Tag Archives: Military

Book Review-Strategic Vision 2030: Security and Development of Andaman & Nicobar Islands

(Published IndraStra Global 24 Aug 2017)

Air Marshal P K Roy and Commodore Aspi  Cawasji, Strategic Vision 2030: Security and Development of Andaman & Nicobar Islands. Pages 177. Vij Books India Pvt Ltd. Delhi, India. ISBN: 978-93-86457-18-9

The book is a topical release during a tense period in geopolitics of the region. The Doklam standoff between China and India, the South China Sea issues and the belligerent stance of North Korea, all have the potential to spark large scale wars in the Indo Pacific.

I have known the authors for a long period and admire them for their professionalism and their ability to put complex strategic issues in the correct perspective. This book represents their expertise in region of the strategic Andaman & Nicobar island territories of India, which sit astride the vital SLOCs leading to the Malacca Straits.

The book has ten chapters apart from the introduction, which provide an all-encompassing perspective in to the islands. These include not only the natural, industrial and economical potential, but also cover the important strategic significance, security issues and policy recommendations. The rise of China as an economic and military power has made significant difference in the Indian Ocean security environment. Its interest in the IOR emerges from the need to secure its energy supply lines and the route for export of its finished goods passing through the IOR. It has been expanding its sphere of influence in the IOR and security of the SLOCs is its priority at present.

Andaman and Nicobar Islands, ANI also face serious internal and non-traditional security threats that could have grave consequences affecting the security environment of ANI. These include terrorism, illegal migration, drug trafficking, proliferation of Weapons of Mass Destruction (WMD), arms smuggling, poaching of natural resources, etc. The book brings out that these islands can be developed as a self-sustaining economic model and rationale of development of both commercial and military infrastructure as a “dual maritime eco-system” to counter Chinese forays in to the Indian Ocean. Security of ANI and its use as a launching pad in shaping the environment of the region must remain a top priority for India.

The book aptly brings in to focus the fact that the connectivity initiatives taken by China on both, the Eastern and Western flanks of India along with the increasing economic relations with ASEAN countries of IOR adjoining Malacca will create a favourable maritime strategic environment for it. China with its modernized PLAN and the support of these logistic nodes will be capable of deploying its major forces in the Indian Ocean within the next five years.

The book recommends that the infrastructure development in terms of ports, jetties, airfields, docking and ship-repair facilities etc must be dual purpose infrastructure serving the needs of civilian as well as the armed forces. There is a need to create a comprehensive economic engagement plan of these islands with the littoral for them to have a stake in its developmental process. Only then such an engagement would allay suspicions amongst them while India enhances the capabilities of ANC and the consequent increased military activity in the region.

The book is a must read for all those who have a need to study strategic complexities of the Andaman & Nicobar Island territories.

Artificial Intelligence and Cyber Defence

 

( Published IndraStra Global 23 Aug 2017)

The current year has seen unprecedented amount of hacker/ransomware attacks on government as well as private enterprises spread all across the world. Shadow Brokers came in form this year by leaking alleged NSA tools, which included a Windows exploit known as EternalBlue. In May, WannaCry ransomware crippled hundreds of thousands of computers belonging to public utilities, large corporations, and private citizens. It also affected National Health Service hospitals and facilities in the United Kingdom. It was halted in its tracks by utilising its flaws and activating a kill switch. WannaCry rode on Shadow Brokers leak of Windows OS weakness EternalBlue and the fact that the Windows MS17-010 patch had not been updated on many machines by the users.  In June, Petya (also known as NotPetya/Nyetya/Goldeneye) infected machines world-wide. It is suspected that its main target was to carry out a cyber-attack on Ukraine. It hit various utility services in Ukraine including the central bank, power companies, airports, and public transportation[1].

In 2009, Conficker[2] worm had infected civil and defence establishments of many nations, for example, the UK DOD had reported large-scale infection of its major computer systems including ships, submarines, and establishments of Royal Navy. The French Naval computer network ‘Intramar’ was infected, the network had to be quarantined, and air operations suspended. The German Army also reported infection of over a hundred of its computers. Conficker sought out flaws in Windows OS software and propagated by forming a botnet, it was very difficult to weed it out because it used a combination of many advanced malware techniques. It became the largest known computer worm infection by afflicting millions of computers in over 190 countries.

It is evident from the above incidents, which have the capability to inflict damage to both military and public institutions, that the amount of data and the speeds at which processing is required in case of cyber defence is beyond the capacity of human beings. Conventional algorithms are also unable to tackle dynamically changing data during a cyber-attack. Therefore, there is an increasing opinion that effective cyber defence can only be provided by real time flexible Artificial Intelligence (AI) systems with learning capability.

The US Defence Science Board report of 2013[3] states that “in a perfect world, DOD operational systems would be able to tell a commander when and if they were compromised, whether the system is still usable in full or degraded mode, identify alternatives to aid the commander in completing the mission, and finally provide the ability to restore the system to a known, trusted state. Today’s technology does not allow that level of fidelity and understanding of systems.” The report brings out that, systems such as automated intrusion detection, automated patch management, status data from each network, and regular network audits are currently unavailable. As far as cyber defence in military is concerned, in the US, it is the responsibility of the Cyber Command to “protect, monitor, analyze, detect, and respond to unauthorized activity within DOD information systems and computer networks”[4]. The offensive cyber operations could involve both military and intelligence agencies since both computer network exploitation and computer network attacks are involved. The commander of Cyber Command is also the Director of National Security Agency, thus enabling the Cyber Command to execute computer exploitations that may result in physical destruction of military or civilian infrastructure of the adversary.

AI utilizes a large number of concepts like, Machine Learning, Fuzzy Logic Control Systems, and Artificial Neural Networks (ANNs), etc. each of which singly or in combination are theoretically amenable for designing an efficient cyber-defence systems. The designed AI cyber defence system should proficiently monitor the network in real time and must be aware of all the activities that the network is engaged in. The system should be able to heal and protect itself. It should have self-diagnostic capabilities and sufficient inbuilt redundancies to function satisfactorily for a specified period of time.

Some advance research work in respect of active cyber defence has been demonstrated under various fields of AI, a few successfully tested examples are:

Artificial Neural Networks- In 2012, Barman, and Khataniar studied the development of intrusion detection systems, IDSs based on neural network systems. Their experiments showed that the system they proposed has intrusion detection rates similar to other available IDSs, but it was at least ~20 times faster in detection of denial of service, DoS attacks[5].

Intelligent Agent Applications-In 2013, Ionita et al. proposed a multi intelligent agent based approach for network intrusion detection using data mining[6].

Artificial Immune System (AIS) Applications- In 2014, Kumar, and Reddy developed a unique agent based intrusion detection system for wireless networks that collects information from various nodes and uses this information with evolutionary AIS to detect and prevent the intrusion via bypassing or delaying the transmission over the intrusive paths[7].

Genetic Algorithm and Fuzzy Sets Applications- In 2014, Padmadas et al. presented a layered genetic algorithm-based intrusion detection system for monitoring activities in a given environment to determine whether they are legitimate or malicious based on the available information resources, system integrity, and confidentiality[8].

Miscellaneous AI Applications- In 2014, Barani proposed genetic algorithm (GA) and artificial immune system (AIS), GAAIS – a dynamic intrusion detection method for Mobile ad hoc Networks based on genetic algorithm and AIS. GAAIS is self-adaptable to network changes[9].

In May, this year it was reported by Gizmodo[10] that over 60,000 sensitive files belonging to the US government were found on Amazon S3 with public access. Amazon S3 is a trusted cloud-based storage service where businesses of all sizes store content, documents, and other digital assets. 28 GB of this data contained unencrypted passwords owned by government contractors (for e.g. Booze Allen) with Top Secret Facility Clearance. It appears that many users had failed to apply the multiple techniques and best practices available to secure S3 Buckets and files.

This month, Amazon became the first public cloud provider to amalgamate Artificial Intelligence with cloud storage to help customers secure data[11]. The new service, Amazon Macie, depends on Machine Learning to automatically discover, classify, alert and protect sensitive data stored in Amazon Web Service, AWS.

From the above it can be seen that there is rapid progress in design and development of cyber defence systems utilizing AI that have direct military and civil applications.

 

[1] https://www.wired.com/story/2017-biggest-hacks-so-far/

[2] http://en.wikipedia.org/wiki/Conficker

[3] Office of the Under Secretary of Defence for Acquisition, Technology and Logistics, Resilient Military Systems and the Advanced Cyber Threat, United States Department of Defence, Defence Science Board, January 2013

[4] U.S. Government Accountability Office, “Defence Department Cyber Efforts,” May 2011, 2–3, http://www.gao.gov/new.items/d1175.pdf.

[5] D. K. Barman, G. Khataniar, “Design Of Intrusion Detection System Based On Artificial Neural Network And Application Of Rough Set”, International Journal of Computer Science and Communication Networks, Vol. 2, No. 4, pp. 548-552

[6] I. Ionita, L. Ionita, “An agent-based approach for building an intrusion detection system,” 12th International Conference on Networking in Education and Research (RoEduNet), pp.1-6.

[7] G.V.P. Kumar, D.K. Reddy, “An Agent Based Intrusion Detection System for Wireless Network with Artificial Immune System (AIS) and Negative Clone Selection,” International Conference on Electronic Systems, Signal Processing and Computing Technologies (ICESC), pp. 429-433.

[8] M. Padmadas, N. Krishnan, J. Kanchana, M. Karthikeyan, “Layered approach for intrusion detection systems based genetic algorithm,” IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), pp.1-4.

[9] F. Barani, “A hybrid approach for dynamic intrusion detection in ad hoc networks using genetic algorithm and artificial immune system,” Iranian Conference on Intelligent Systems (ICIS), pp.1 6.

[10] http://gizmodo.com/top-defence-contractor-left-sensitive-pentagon-files-on-1795669632

[11] https://www.forbes.com/sites/janakirammsv/2017/08/20/amazon-brings-artificial-intelligence-to-cloud-storage-to-protect-customer-data/#465ef0ef7432

Initiatives for Clean and Green Indian Navy

(Published in IndraStra Global 07 Aug 2017) 

On 12 February 2017, INS Sarvekshak, a survey ship of the Indian Navy had completed installation of a 5KW solar power system on board[1]. It is estimated that in this project, the profit generated would be Rs. 2.7 Cr, taking the service life of the ship to be about 25 years. This solar power installation avoids 60,225 kg of carbon a year and saves 22,995 liters of diesel.

Green Energy Generation Options to Defense Forces

Green Energy options that are available to defense forces depending upon their geographical locations include a combination of the following:

Solar Energy. Solar energy is being utilized by the forces to reduce load on traditional generators. Solar energy can be generated using both fixed and portable solar systems to provide a clean source of energy especially at remote locations. This also helps in reducing the number of costly and at times dangerous fuel re-supply missions. With the rapidly reducing costs of PV cells, the rates of solar power are highly competitive. Further, since the PV cells are much lighter they can be easily carried on the backpacks in battlefield.

Biomass. Developments in Biomass have resulted in corn-based ethanol and soybean or canola based biodiesel. Lately, however there is shift away from food crops for generating fuel towards use of lignocelluloses feed stocks and energy crops that can be grown on wastelands. The biomass to liquids (BTL) includes synthetic fuels derived thermo-chemically via biomass gasification and cellulosic ethanol produced biochemically. The production of Fischer-Tropsch liquids (FTL)[2] from biomass is considered advantageous over cellulosic ethanol.

Fuel Cells. Fuel cells are one of the most efficient techniques for power generation and an alternate to petroleum. They can function on a number of different fuel sources like biogas, hydrogen, or natural gas. They also provide scalable advantage from megawatts down to a watt, which enable meeting a large variety of applications for the forces. They can power transportation systems on land and sea, provide power in remote areas, act as power backups, assist in distributed power, and so on. The byproducts of fuel cells are water and heat since they directly convert chemical energy in hydrogen to electricity. They are also highly efficient with conversion in the range of ~60%, which is nearly twice that of conventional sources.

Waste to Energy. Municipal Solid Waste (MSW) can be converted to energy in three ways, namely, pyrolysis, gasification, and combustion. These processes are differentiated by the ratio of oxygen supplied to the thermal process divided by oxygen required for complete combustion. It has been observed that a localized approach to generating energy from waste is beneficial as compared to a large facility located miles away. This helps in reducing the overall carbon footprint as well as facilities that do not look out of place.

Hydropower. Investments in small hydropower systems reduce the exposure to fuels considerably. Intelligently sited and planned systems assure clean and reliable energy over the years.

Marine Renewable Energy. A large source of renewable energy is presented by the oceans, in form of wind driven waves on the coast, ocean currents, ebbing and flowing tidal currents through inlets and estuaries, river currents, offshore wind energy and ocean thermal systems. All of these can be utilized for power generation by the forces.

Geothermal Power. It provides a number of advantages like, it is non-interruptible, it is cleaner, it is an established technology, and is abundant. This is a highly suitable energy source for land-based establishments that have access to it.

Green Initiative-US Navy

The US Navy had set the goals of energy efficient acquisitions, reducing the non-tactical petroleum use by 50 % by 2015 and sailing the Great Green fleet by 2016.Further, it had decided upon producing 50% of shore based energy from alternate sources, making 50 % installations net-zero by 2020, and lastly, ensuring that by 2020, 50% of its total energy requirements would be met from alternate energy sources.

The Great Green Fleet Initiative of the US Navy. The Great Green Fleet is a demonstrator of the strategic and tactical viability of bio fuels. A strike group had embarked on a yearlong deployment in West Pacific in January 2016. The strike group (JCSSG) consisted of USS John C. Stennis with Carrier Air Wing (CVW-9) and Destroyer Squadron (DESRON) 21 embarked, guided-missile cruiser Mobile Bay and guided missile destroyers Chung-Hoon, Stockdale, and William P. Lawrence. CVW-9 consisted of Helicopter Maritime Strike Squadron (HSM) 71; Helicopter Sea Combat Squadron (HSC) 14; Airborne Early Warning Squadron (VAW) 112; Electronic Attack Squadron (VAQ) 133; Fleet Logistics Combat Support Squadron (VRC) 30, Detachment 4 and Strike Fighter Squadrons (VFA) 151, 97, 41 and 14[3]. The JCSSG had used alternate fuel (10 percent beef tallow and 90 percent marine diesel) and incorporated energy conservation measures. The Great Green Fleet initiative also included use of energy efficient systems and operating procedures like changing of lights to solid-state lighting, temperature control initiative, installation of stern flaps to reduce drag etc.

Green Initiative -Indian Navy

In order to reduce the carbon footprint of the Indian Defense Forces and associated establishments the Government of India has initiated considerable efforts under phase-II/III of the Jawaharlal Nehru National Solar Mission JNNSM. It includes setting up over 300 MW of Grid-Connected Solar PV Power Projects by Defense Establishments under Ministry of Defense and Para Military Forces with Viability Gap Funding under JNNSM. As per the annual report of Ministry of New and Renewable Energy (MNRE) for the year 2014-2015[4], some of the salient features of the scheme include:

-A capacity of 300 MW to be set up in various Establishments of Ministry of Defense with the minimum size of the project to be one MW. The defense establishments would identify locations for developing solar projects, anywhere in the country including border areas from time to time. The projects under this Scheme will mandatorily use solar cells/modules, which are made in India. The Defense organizations/Establishments will be free to own the power projects i.e. get an Engineering, Procurement, Construction (EPC) contractor to build the project for them or get a developer who makes the investment and supplies power at a fixed tariff of Rs.5.50 per unit for 25 years. The MoD or the Defense Organization would be free to follow their own procurement systems or develop detailed guidelines or procedures for tendering.

-Inter-Ministerial group has recommended National Clean Energy Fund (NCEF) Support of Rs. 750 cr.

Indian Navy has completed three years of its Green Initiatives Program on World Environment Day in 2017. Smart LED lighting in Naval stations is also being adopted on its warships. Navy has undertaken a large number of green measures to reduce its overall carbon footprint. An Energy and Environment Cell[5] at Naval Headquarters has been created to monitor the implementation of the green energy programs. The Navy has initiated efforts to go green in ship designs as well as its operations. It also carries out mass awareness drives in its dockyards, and shore establishments to sensitize the personnel to energy conservation.

The Navy has set a target of 19 MW Solar PV installation[6],  in line with the National Mission of Mega Watt to Giga Watt towards achieving 100 GW Solar PV installations by 2022. Navy has also pledged 1.5 per cent of its Works budget towards Renewable Energy generation. Navy is exploring the feasibility of exploiting Ocean Thermal Energy and Wave Energy as sources of green energy.

 

[1] INS Sarvekshak goes green; installs solar power system. Indian Express,12 February 2017.

http://indianexpress.com/article/india/ins-sarvekshak-goes-green-instals-solar-power-system-4520969/ (Accessed 29 Jul 2017)

[2] James T. Bartis &Lawrence Van Bibber. Alternative Fuels for Military Applications. RAND Corporation, 2011, Santa Monica. https://www.rand.org/content/dam/rand/pubs/monographs/2011/RAND_MG969.pdf (Accessed 30 Jul 2017)

[3]  The Great Green Fleet Explained. Military Spot, 27 Jun 2016.  http://www.militaryspot.com/news/great-green-fleet-explained  (Accessed 29 Jul 2017)

[4] Annual Report 2014-2015, Ministry of New and Renewable Energy, Government of India. http://mnre.gov.in/file-manager/annual-report/2014-2015/EN/Chapter%204/chapter_4.htm (Accessed 30 Jul 2017)

[5] Indian Navy Pledges 1.5 Per Cent of its Works Budget Towards Renewable Energy Generation. Press Information Bureau, Government of India, Ministry of Defence, 05-June-2016. http://pib.nic.in/newsite/PrintRelease.aspx?relid=145978 (Accessed 01Aug 2017)

[6] Initiatives for Clean and Green Navy. Indian Navy.

https://www.indiannavy.nic.in/content/initiatives-clean-and-green-navy/page/0/1 (Accessed 01 Aug 2017)

Massive Ordnance Air Blast, MOAB – A Perspective

(Published in CASS Journal, Vol4, No.3. Jul-Sep 2017. ISSN 2347-9191)

On 13th April 2017 at 7:32 p.m. local time[1], U.S. Forces Afghanistan conducted a strike using a GBU-43/B Massive Ordnance Air Blast bomb, MOAB dropped from an U.S. aircraft on an ISIS (Khorasan) tunnel complex in Achin district, Nangarhar province, Afghanistan. Some of the immediate reactions were: –

-Mr Ashraf Ghani, the president of Afghanistan, said that the strike was “designed to support the efforts of the Afghan National Security Forces (ANSF)” and “precautions were taken to avoid civilian casualties”[2],

-Mr Hamid Karzai, Afghanistan’s former president condemned the attacks in a series of tweets saying “This is not the war on terror but the inhuman and most brutal misuse of our country as testing ground for new and dangerous weapons”[3]

In January 2015, the ISIS had announced the establishment of its Khorasan branch, it was also the first time the ISIS had officially spread its wings outside the Arab world. In December 2015, analyst Harleen Gambhir of Institute for the Study of War, ISW had indicated that ISIS is likely to expand in Afghanistan- Pakistan region[4] as ISIS associate Wilayat Khorasan, controlling Nangarhar province, had commenced attacking Kabul and Jalalabad. It was estimated that ISIS influence is likely to increase further due to many factors such as, infighting among Taliban, vacuum due withdrawal of international forces and reduction in competition with al-Qaeda due to support of Khorasan.

Nangarhar Province is located in eastern Afghanistan, on the Afghanistan – Pakistan border. It is bordered by Kunar and Laghman provinces in the north, Pakistan in the east and south, and Kabul and Logar provinces in the west. It provides the easiest passage to Pakistan from Afghanistan. Topographical Features of Nangarhar include Spin Ghar and Safed Mountain Ranges along the southern border; belt of forests along southern mountain ranges and in Dara-I-Nur District in north; Khyber Pass in Mahmund Dara District in east; bare soil, and rocky outcrop throughout centre of the province. Achin, the target of the MOAB on 13 April 2017, is one of the districts in southern Nangarhar, bordering Pakistan.

The ISIS (K) were using a tunnel and cave complex in Tora Bora area which was apparently created by Central Intelligence Agency, CIA for the Mujahideen in 1980 in their fight against the Soviets. Tora Bora has steep heights, mountains, valleys and caves. The Tora Bora CIA complex constitutes of miles of tunnels, bunkers and camps built with the financial support of CIA 35 miles south west of Jalalabad[5]. It is understood that the complex was built by the Saudi Binladen group and the young Osama bin Laden had played a big role in its construction. The complex is said to have its own ventilation and hydroelectric power supply system.  Subsequently Osama bin Laden had hidden in the same tunnel complex before escaping to Pakistan during attack on Tora Bora. The MOAB was dropped on the same mountain ridge in the Achin district of Nangarhar.[6]

Conventional/Incendiary/Fuel Air Explosive/Thermobaric Bombs

It is required to differentiate between conventional, incendiary, Fuel Air Explosive and Thermobaric bombs because MOAB is compared with different types of Bombs like the Russian 15, 650-pound Aviation Thermobaric Bomb of Increased Power (ATBIP) also called the FOAB (father of all bombs), as well as the 30,000-pound GBU-57A/B Massive Ordnance Penetrator (MOP).

Conventional Bombs. A conventional bomb is a metal casing filled with high explosives (HE). Conventional bombs are generally classified according to the ratio of explosive to total weight. They are mainly of three types namely general purpose or GP, penetration and cluster bombs (The Convention on Cluster Munitions (CCM) is an international treaty that has prohibited the use, transfer, and stockpiling of cluster bombs, which scatters submunitions (“bomblets”) over an area). A GP bomb produces a combination of blast and fragmentation effects with weight of its explosive filling approximately equal to half of its total weight. In the fragmentation bomb the explosive filling is up to 20% of its total weight, with fragmentation cases making up the remaining weight. The damage is caused due to fragments travelling at high velocities. The penetration bombs have up to 25/30% of explosive filling and remaining is taken up by the body designed for penetration.  The kinetic energy of the bomb or the shaped charge or a combination of both achieve the penetration of the target.

Incendiary Explosives. Incendiaries cause damage by fire. They are used to burn supplies, equipment, and structures.

Fuel Air Explosives FAE. These disperse an aerosol cloud of fuel ignited by a detonator to affect an explosion. The wave front expands rapidly due to overpressure and flattens objects in the vicinity of the FAE cloud, and also causes heavy damage in the neighbouring area. A FAE bomb contains fuel and two independent explosive charges. After deployment, the first explosive charge is used to burst open the fuel container at a predetermined height and disperse the fuel. The fuel disperses and mixes with atmospheric oxygen and flows around the target area. The second charge is then made to detonate the cloud, which creates a massive blast wave. The blast wave results in extensive damage to the target especially in enclosed spaces.

Thermobaric weapons. Thermobaric weapons have been designed to overcome the short comings of conventional weapons when used against fortified structures/buildings. The blast wave generated by thermobaric weapons are not designed for penetration and it is effective in causing blast damage in a large radius. Fuels are chosen on the basis of the exothermicity of their oxidation, ranging from powdered metals, such as aluminium or magnesium, to organic materials, possibly with a self-contained partial oxidant. During detonation of a high explosive bomb, rapid formation of a blast wave, thermal radiation, break-up of the munition casing, and acceleration of the fragments takes place. In the case of conventional blast/fragmentation warheads, a large part of the energy is consumed by the breaking-up of the shell and acceleration of the fragments. Thermobaric weapons have thin casings and maximum energy is released in a couple of microseconds as a blast/shock wave. In the initial detonation only a small part of energy gets released, the products of detonation thereafter suck oxygen from the air and burn in what is termed as after-burning[7]. This increases the blast pressure wave as well as the fire envelope.

Guidance of Bombs

Air to surface bombs today have either laser guidance kits or Global Positioning System, GPS guidance kits. The laser guided bombs were found to be difficult to deploy in bad weather/visibility conditions or when the targets could not be safely illuminated by the designator, and this led to the preference for GPS guided munitions. Munitions with integrated Inertial Navigation System, INS coupled to a GPS receiver like the Joint Direct Attack Munition (JDAM) of Boeing are all weather deployable. The GPS/INS coupled with a tail control system provide the guidance. The Aircraft provides the initializing position and velocity, the target coordinates are also fed/updated by the aircraft through a data link. With GPS, the bomb gives a circular error probable (CEP) of five meters and without the GPS (signal lost/not available/jammed) for flight times up to 100 seconds the CEP is 30 meters. Thus, the GPS/INS kits have enabled the bombs to have the following advantages[8]:

  • Deployable in all weather conditions.
  • Fire and forget capability, the aircraft can proceed to its next task after launch.
  • Enhanced Launch Acceptance Region or LAR because these kits enable the weapon to adjust the flight trajectory at the time of launch to hit the target.
  • GPS provides an accurate common time code for all systems.
  • Flight trajectory can be programmed to hit the target at desired angle of impact.

As a further improvement Laser JDAM is now operational which has an add on laser kit in addition to the GPS/INS to take care of manoeuvring targets and midcourse alterations. A new wing kit (extended range- ER) can also be added to extend the range of the bomb up to 38 nm.

The MOAB – ‘Mother of All Bombs’

The GBU-43/B (MOAB) is a large, powerful and accurately delivered conventional bomb. It has KMU-593/B GPS-guidance with fins and inertial gyro for pitch and roll control. The KMU-593/B kits have been further upgraded with SAASM (Selective Availability/Anti-Spoofing Module) technology in the GPS receivers. In a further improvement, the KMU-xxx/C kits are additionally fitted with Anti-Jam technology. The MOAB is a satellite guided improved version of the 15000-pound BLU-82 Daisy Cutter bomb. It is 30 feet in length with a diameter of 40.5 inches. The warhead is a BLU 120-B aluminium casing weighing 3000 pounds with an explosive weight of 18,700 pounds. The warhead is designed for blast effect. It was designed to be delivered by a C-130 and originally used the explosive Tritonal, a mixture of 80% Tri nitro toluene, TNT and 20% aluminium powder. It was first tested in March 2003 at Eglin Air Force Base in Florida, when it produced a mushroom cloud that could be seen up to 20 miles away[9]. The current explosive filling is 18,700 pounds of H6. H6 is a type of HBX explosive composition, which is a cast able military explosive mixture composed of 44.0% RDX (Cyclotrimethylene trinitramine), 29.5% TNT and 21.0% powdered aluminium by weight. The MOAB delivers a massive explosive blast (over pressure), with lesser fragmentation effects due to a thin-walled aluminium casing. MOAB is a good choice against caves and earthen tunnels since the pressure waves on entering the complex can severely injure personnel and collapse the structures. The MOAB provides a capability to perform psychological operations, attack large area targets, or hold at-risk threats hidden within tunnels or caves. It is not designed for deep penetration and is an area impact weapon.

The MOAB is cradle launched from C-130 Hercules or MC-130 Talon II aircraft by means of a drogue extraction parachute. [10] Thereafter, the MOAB is guided for approximately 3 nautical miles through a GPS system (with inertial gyros for pitch and roll control), JDAM actuators, and is stabilized by series of fixed wings and grid fins.  The MOAB does not use a retarding parachute, thus permitting the aircraft to fly at higher altitudes, and making it safer for US pilots.

Future Trends in Design and Development of Conventional Bombs

It is understood that nanotechnology is spearheading the development of highly potent explosives, however, not much information is available through open sources, much of it has to be gleaned from research papers and patents (for e.g. Patents like US20150210605 – Structure of energetic materials, US6955732 – Advanced thermobaric explosive compositions and WO2013119191A1 – Composition for a fuel and air explosion).

Essentially, Nano energetic materials (nEMs) perform better than conventional materials because of much larger surface area, which increases speed of reaction and larger energy release in much shorter time. Addition of Super thermites[11] (nano-aluminium based) have shown instantaneous increase in explosive power of existing compositions[12]. Further, use of nano-sized materials in explosives has significantly increased safety and insensitivity by as much as over 30% without affecting reactivity. It is predicted that nEMs would provide the same explosive power at mass up to two orders of magnitude less than the current explosive systems[13].

While Nanosizing of high explosives leads to increasing their explosive power[14] and decreasing their sensitivity to external forces[15], it also decreases its thermal stability. The shelf life of such explosives could therefore stand reduced; however, some patents reveal that this issue has also been resolved technically (e.g. patent US20120227613 Thermal enhanced blast warhead). In India, the work on explosives and propellants is being undertaken at High Energy Materials Laboratory, HEMRL, a Defence Research and Development Organisation, DRDO laboratory, and it is understood that the research in nEMs is progressing satisfactorily.

It can be envisaged that nEMs would replace the conventional explosives in the next decade. This would provide existing conventional weapons with explosive powers higher in magnitude by a factor of two and enhance the safety to external stimulation by at least 30%. In simple terms, a missile warhead having an explosive content of 200 kg of TNT equivalent would have an explosive power of 20,000 kg of TNT equivalent when substituted with nEMs material of same weight of 200 kg! This advancement could displace Tactical nukes from the battlefield.

Nanotechnology is permeating in all fields of design & manufacturing of weapons and ammunition. It is bringing unprecedented precision in weapon systems, robustness in triggering mechanisms and opening new frontiers in propellant and pyrotechnic functioning. In addition to explosive and propellants, Nanomaterials have ushered in innovative improvements in many characteristics of ammunition such as guidance, penetration capacity, embedded sensors for monitoring condition, embedded antennae for guidance and so on.

Russian Answer to MOAB

An Aviation Thermobaric Bomb of Increased Power (ATBIP) was tested by Russia on 11 September 2007. It was said to be the most powerful conventional bomb in the world, with a 7-Ton explosive mixture resulting in a devastating effect equivalent to 44 tons of TNT[16]. It was nicknamed the Father of All Bombs (FOAB). It was hinted that the FOAB contained a liquid fuel, such as ethylene oxide, mixed with energetic nano-aluminium powder, which was dispersed by a high explosive booster. Some reports speculated that the liquid fuel was purified using nano-filters. What caught the imagination of defense experts was the fact that the Russian FOAB had less fuel than the MOAB, but was four times more powerful. It was also probably the first time that the nonprofessional learned of the lethal uses of nanotechnology.

India’s Biggest Conventional Bomb – SPICE

India has acquired the 2000 pound Israeli SPICE (Smart, Precise Impact, Cost-Effective) bomb. It is the biggest bomb in the inventory of the Indian Airforce. Israel’s Rafael Advanced Defence System’s first precision guidance kit for dumb bombs was called the SPICE. SPICE kits claim a CEP (Circular error probable) of three metres. SPICE’s Automatic Target Acquisition capability works by comparing a real-time image received from the dual Charge-Coupled Device (CCD) and infrared seeker to a reference image stored in the weapon’s computer. The SPICE can be carried on Mirage 2000 as well as on a variant of SU-30 MK1 aircraft of the Indian Air Force. The SPICE-2000 is stated to have a stand-off range of 32.3nm (60km).

MOAB the New WMD?

‘In the more distant future, weapons systems based on new principles (beam, geophysical, wave, genetic, psychophysical and other technology) will be developed. All this will, in addition to nuclear weapons, provide entirely new instruments for achieving political and strategic goals. Such hi-tech weapons systems will be comparable in effect to nuclear weapons but will be more “acceptable” in terms of political and military ideology. In this sense, the strategic balance of nuclear forces will play a gradually diminishing role in deterring aggression and chaos.[17]

Vladimir Putin, 2012

There are differing definitions of weapons of mass destruction WMD, therefore it is better to adhere to the one adopted by the United Nations. The definition of WMD was arrived at by the United Nations Convention on Conventional Armament in its first resolution in 1948.The Commission advised the Security Council that “all armaments and armed forces, except atomic weapons and weapons of mass destruction fall within its jurisdiction” and also stated that “weapons of mass destruction should be defined to include atomic explosive weapons, radioactive material weapons, lethal chemical and biological weapons, and any weapons developed in the future which have characteristics comparable in destructive effect to those of the atomic bomb or other weapons mentioned above”.[18] This definition provides the guidelines to distinguish between the conventional weapons and the WMDs.

The determining factors distinguishing the Conventional weapons from the WMD could be the terms Mass Causalities and Mass Destruction. However, mass casualties can also be inflicted by conventional weapons during extended periods of siege or carpet bombings. There is ambiguity in the sense that that event of occurrence of mass casualties could be a single event or a series of consecutive events. The number of casualties could in fact be higher in sustained usage of conventional weapons than in the case of a single use WMD. The other notable point is that there is no quantification of the term ‘Mass’, i.e. how many dead humans would qualify for an event to be termed as Mass casualty. The term mass destruction also suffers from similar dichotomy.  A barrage of conventional weapons can cause a larger scale physical destruction spread across tens of miles as compared to a single WMD in a single event, again, quantification as to what constitutes Mass Destruction has not been defined clearly.

The MOAB has been incorrectly compared to a nuclear bomb. It has less than 1000th[19] of the power of the atomic bomb ‘Little Boy’ dropped on Hiroshima because the MOAB blast was equivalent to 11 tons of TNT whereas the Hiroshima blast was close to 13000 tons equivalent of TNT.  The ‘Fat Man’ atomic bomb dropped on Nagasaki was a 20,000 tons equivalent of TNT. However, the blast radius of MOAB lies in the same one mile radius as the atomic bombs of WWII. Conventional bombs can never achieve the damage potential of the exponential rise of energy that ensues upon a nuclear bombs detonation. The most powerful of nuclear bombs today is the B83 bomb of the United States, it uses a fission process similar to that used in the atomic bombs, the initial energy is then used to ignite a fusion reaction in a secondary core of the hydrogen isotopes deuterium and tritium. The nuclei of the hydrogen atoms fuse together to form helium, and result in a chain reaction leading to a far more powerful explosion. The nuclear fission bomb B83, has a blast equivalent to 1,200,000 tons of TNT compared to 11 tons equivalent of TNT blast by the MOAB. The tactical nuclear weapons range from 10 tons to 100 kilotons. What unambiguously differentiates a conventional weapon from a WMD would be the latent effects of the deployment, which in case of atomic/nuclear weapons last across generations in case of humans and decades in case of remediation of the material. The UN definition of WMD covering atomic, radiological, chemical, biological, or any weapon producing similar effects appears to be sustainable, from this it can be inferred that MOAB/FOAB type of conventional bombs; which lie on the lowest limits of the destructive power of tactical nukes without the attendant latent effects; would not fall in the category of WMD.

An U.S. Air Force Special Operations Command MC-130 Combat Talon transport aircraft dropped the MOAB out of the cargo ramp on 13th April 2017.The bomb detonated at 7.32 pm local time in the Achin district of the eastern province of Nangarhar[20].  The Guardian reported that “a local security official said they had requested a large strike because fighter jets and drones had failed to destroy the tunnel complex”. Also, Ismail Shinwari, the district governor of Achin, said, “the strike was closely coordinated with Afghan soldiers and special forces, and tribal elders had been informed to evacuate civilians.[21] He also told AFP that that at least 92 ISIL fighters were killed in the bombing.[22] It was confirmed later by the Afghan officials that foreign militants, including 13 Indians, were also killed in the bombing.[23] The Indians had joined ISIS and were fighting for caliphate.

The MOAB had proved itself in Global War on Terror.

 

[1] U.S. Bombs, Destroys Khorasan Group Stronghold in Afghanistan. U.S. Department of Defense. 13 April 2017. https://www.defense.gov/News/Article/Article/1151139/us-bombs-destroys-khorasan-group-stronghold-in-afghanistan/ (Accessed 25 May 2017)

[2] D’Angelo, Bob. “Afghan official: 36 ISIS fighters killed by ‘MOAB’”. ajc.com. 14 April 2017. http://www.ajc.com/news/military/afghan-official-isis-fighters-killed-moab/2eZENK0N1wpZNmp2OJZJaK/ (Accessed 28 May 2017)

[3] “U.S. drops ‘mother of all bombs’ in Afghanistan, marking weapon’s first use”. CBS News. 13 April 2017. http://www.cbsnews.com/news/us-drops-mother-of-all-bombs-in-afghanistan-marking-weapons-first-use/ (Accessed 03 Jun 2017)

[4] Harleen Gambhir, ISIS in Afghanistan: ISW Research. 3 December 2015.

http://iswresearch.blogspot.in/2015/12/isis-in-afghanistan-december-3-2015.html (Accessed 28 May 2017)

[5] Weaver, Mary Anne. “Lost at Tora Bora”. The New York Times. 11 September 2005. http://www.nytimes.com/2005/09/11/magazine/lost-at-tora-bora.html (Accessed 25 May 2017).

[6] Robertson, Nic (2017-14-04) MOAB hit caves used by ISIS, drug smugglers and Osama bin Laden. CNN.

http://edition.cnn.com/2017/04/13/asia/afghanistan-moab-target-robertson/index.html (Accessed 03 Jun 2017)

[7] Dr Anna E Wildegger-Gaissmaier. Aspects of thermobaric weaponry. ADF Health Vol 4 April 2003.

http://www.defence.gov.au/health/infocentre/journals/ADFHJ_apr03/ADFHealth_4_1_03-06.pdf (Accessed 25 May 2017)

[8] Attariwala, Joetey. Dumb Bombs with Graduate Degrees, Armada International. 27April 2017.

https://armadainternational.com/2017/04/dumb-bombs-with-graduate-degrees/ (Accessed 28 May 2017)

[9] Mizokami, Kyle. U.S. Air Force Drops the Largest Conventional Bomb Ever Used in Combat. 13Apr 2017. http://www.popularmechanics.com/military/weapons/news/a26055/us-air-force-drops-moab-isis/ (Accessed 03 Jun 2017)

[10] GBU-43/B “Mother of All Bombs”, http://www.globalsecurity.org/military/systems/munitions/moab.htm (Accessed 05 Jun 2017)

[11] Nano-Thermite or Super-Thermite is a metastable intermolecular composite (MICs) containing an oxidizer and a reducing agent, which are intimately mixed on the nanometer scale. This dramatically increases the reactivity relative to micrometer -sized powder thermite. MICs, including nano-thermitic materials, are a type of reactive materials investigated for military use, as well as for general applications involving propellants, explosives, and pyrotechnics.

[12] Gartner, John. “Military Reloads with Nanotech.” Technology Review, an MIT Enterprise, 21 January 2005. http://www.technologyreview.com/computing/14105/page1/ (Accessed 25 May 2017)

[13] Yang, Guangcheng, Fude Nie, Jinshan Li, Qiuxia Guo, and Zhiqiang Qiao. “Preparation and Characterization of Nano-NTO Explosive.” Journal of Energetic Materials, 25, 2007.

[14] Kaili Zhang, Carole Rossi, and G.A. Ardila Rodriguez. “Development of a Nano-Al/CuO Based Energetic Material on Silicon Substrate.” Applied Physics Letters No. 91, 14 September 2007.

[15] Guangcheng Yang, Fude Nie, Jinshan Li, Qiuxia Guo, and Zhiqiang Qiao. “Preparation and Characterization of Nano-NTO Explosive.” Journal of Energetic Materials, 25, 2007.

[16] Russia tests giant fuel-air bomb. BBC. 12 Sep 2007. http://news.bbc.co.uk/2/hi/europe/6990815.stm / (Accessed 28 May 2017)

[17] Vladimir Putin, “Being Strong: National Security Guarantees for Russia,” Rossiiskaya Gazeta, February 20, 2012, http://archive.premier.gov.ru/eng/events/news/18185// (Accessed 25 May 2017)

[18] Commission on Conventional Armaments (CCA), UN document S/C.3/32/Rev.1, August 1948, as quoted in UN, Office of Public Information, The United Nations and Disarmament, 1945–1965, UN Publication 67.I.8, 28.

[19] Tayag, Yasmin. How Does the “Mother of All Bombs” Compare to a Nuclear Bomb? 13 April 2017. https://www.inverse.com/article/30306-moab-mother-of-all-bombs-compare-nuclear-atomic-bomb-hiroshima-nagasaki (Accessed 03 Jun 2017)

[20] Ackerman, Spencer; Rasmussen, Sune Engel (14 April 2017). “36 Isis militants killed in US ‘mother of all bombs’ attack, Afghan ministry says”. The Guardian. https://www.theguardian.com/world/2017/apr/13/us-military-drops-non-nuclear-bomb-afghanistan-islamic-state (Accessed 28 May 2017)

[21] Rasmussen, Sune Engel. “‘It felt like the heavens were falling’: Afghans reel from MOAB impact”. The Guardian. 14 April 2017.  https://www.theguardian.com/world/2017/apr/14/it-felt-like-the-heavens-were-falling-afghans-reel-from-moabs-impact?CMP=share_btn_tw (Accessed 25 May 2017).

[22] “IS death toll hits 90 from huge US bomb in Afghanistan”. Times Live. 15 April 2017. http://www.timeslive.co.za/world/2017/04/15/IS-death-toll-hits-90-from-huge-US-bomb-in-Afghanistan (Accessed 05 Jun 2017)

[23] “13 suspected Indian IS fighters killed as MOAB hit Afghanistan: Reports”. Hindustan Times. 18 April 2017. http://www.hindustantimes.com/india-news/13-suspected-indian-is-fighters-killed-as-mother-of-all-bombs-hit-afghanistan-reports/story-q0klSwa0SH2CocXkyHMAWK.html (Accessed 03 Jun 2017)

 

Green Energy Initiatives by Defence Forces

(Abridged version published in SP’s Military Year Book 2017)

“Unleashing war fighters from the tether of fuel and reducing our military installations’ dependence on a costly and potentially fragile power grid will not simply enhance the environment; it will significantly improve our mission effectiveness.”

Dorothy Robyn, former deputy undersecretary of defense, in testimony before the Senate Energy and Natural Resources Committee, May 20, 2010.[1]

 

Military fuel consumption studies have highlighted various issues afflicting an assured supply of fuel to forces during extended operations especially in regions far away from the country of origin. Fuel is procured from agencies near to the operational areas to reduce the logistic supply chain. This is however subject to prevailing prices and fluctuations from time to time. It makes it difficult to make budgetary provisions for this essential commodity. In addition to the cost of transportation, attacks on the convoys carrying fuel are also a common feature in areas like Afghanistan and Iraq, this leads to loss of essential fuel supplies as well as combat manpower.These problems have a cascading effect on mobility of heavy military equipment as well as battle command stations, so much so that the logistic chain has to be put in place prior to the move to ensure operability of the equipment.

NATO[2] has brought out that the fact that; its forces consumed up to 4 gallons for transporting each gallon of fuel to Afghanistan; about   3000 US soldiers were killed /wounded from 2003 to 2007 in attacks on fuel and water convoys in Iraq and Afghanistan; and that there is one casualty for every 24 fuel re-supply convoys to Afghanistan. In a military camp, about 60/70% of fuel is used to produce electricity to heat/cool water or air. Further, a conventional diesel generator is able to convert only one third of its input energy in to electricity with the remaining being lost as heat. The U.S. military had begun to reduce its dependence upon fossil fuels proactively by 2010. It commenced development, evaluation, and deployment of renewable energy sources to decrease its carbon footprint.

The US Secretary of Defense delivered the review of the Department of Defense (DOD) strategy and priorities to Congress on March 4,2014 vide the 2014 Quadrennial Defense Review[3] (QDR).This included the affect of   rebalance to Asia upon force structure, weapons systems, platforms, and operations. The highlights were,  “Positioning additional forward-deployed naval forces to achieve faster response times at a lower recurring cost; Deploying new combinations of ships, aviation assets, and crisis response forces that allow for more flexible and tailored support to the regional Combatant Command; Developing concepts, posture and presence options, and supporting infrastructure to exploit the Department’s investment in advanced capabilities; and Pursuing access agreements that provide additional strategic and operational flexibility in case of crisis” .  It was evident that the shift would imply requirement of additional logistic arrangements in the fuel provisioning chain. It has been estimated that the Asia-Pacific shift would entail an eleven percent additional operational fuel demand on the US DOD.

The European Defence Agency, EDA, has launched the ‘Military Green’ initiative. It has been estab­lished by six countries namely, Austria, Cyprus, Czech Republic, Greece, Germany, and Luxembourg. The project visualizes access rights to rooftops and land in military premises being offered to the market for electricity production using photovoltaic technology. The electricity produced would supply the defense locations as well as feed the surplus green energy to the local grid.

NATO constituted a “Smart Energy Team” (SENT), which examined national and NATO documents and visited defense agencies to identify energy efficient solutions for incorporation into NATO’s standards and best practices. The team concluded that ‘Reducing fuel consumption in the military is an operational imperative. Smart Energy solutions cannot only save money when less fuel is used, but can also save soldier’s lives, and help improve the mobility, as well as the resilience and endurance of military forces’[4].

Thus, it can be seen that it became imperative for the major defense forces to give impetus to adoption of renewable energy sources in their routine as well as operational deployments.

Green Energy Generation Options to Defense Forces

Green Energy options that are available to defense forces depending upon their geographical locations include a combination of the following:

Solar Energy. Solar energy is being utilized by the forces to reduce load on traditional generators. Solar energy can be generated using both fixed and portable solar systems to provide a clean source of energy especially at remote locations. This also helps in reducing the number of costly and at times dangerous fuel re-supply missions. With the rapidly reducing costs of PV cells, the rates of solar power are highly competitive. Further, since the PV cells are much lighter they can be easily carried on the backpacks in battlefield.

Biomass. Developments in Biomass have resulted in corn-based ethanol and soybean or canola based biodiesel. Lately, however there is shift away from food crops for generating fuel towards use of lignocelluloses feed stocks and energy crops that can be grown on wastelands. The biomass to liquids (BTL) includes synthetic fuels derived thermo-chemically via biomass gasification and cellulosic ethanol produced biochemically. The production of Fischer-Tropsch liquids (FTL)[5] from biomass is considered advantageous over cellulosic ethanol.

Fuel Cells. Fuel cells are one of the most efficient techniques for power generation and an alternate to petroleum. They can function on a number of different fuel sources like biogas, hydrogen, or natural gas. They also provide scalable advantage from megawatts down to a watt, which enable meeting a large variety of applications for the forces. They can power transportation systems on land and sea, provide power in remote areas, act as power backups, assist in distributed power, and so on. The byproducts of fuel cells are water and heat since they directly convert chemical energy in hydrogen to electricity. They are also highly efficient with conversion in the range of ~60%, which is nearly twice that of conventional sources.

Waste to Energy. Municipal Solid Waste (MSW) can be converted to energy in three ways, namely, pyrolysis, gasification, and combustion. These processes are differentiated by the ratio of oxygen supplied to the thermal process divided by oxygen required for complete combustion. It has been observed that a localized approach to generating energy from waste is beneficial as compared to a large facility located miles away. This helps in reducing the overall carbon footprint as well as facilities that do not look out of place.

Hydropower. Investments in small hydropower systems reduce the exposure to fuels considerably. Intelligently sited and planned systems assure clean and reliable energy over the years.

Marine Renewable Energy. A large source of renewable energy is presented by the oceans, in form of wind driven waves on the coast, ocean currents, ebbing and flowing tidal currents through inlets and estuaries, river currents, offshore wind energy and ocean thermal systems. All of these can be utilized for power generation by the forces.

Geothermal Power. It provides a number of advantages like, it is non-interruptible, it is cleaner, it is an established technology, and is abundant. This is a highly suitable energy source for land-based establishments that have access to it.

Initiatives by Defence Forces

“Today’s war fighters require more energy than at any time in the past and that requirement is not likely to decline,” he explained. “During World War II, supporting one Soldier on the battlefield took one gallon of fuel per day. Today, we use over 22 gallons per day, per Soldier.”

General Martin E. Dempsey

The US Department of Defense (DOD) published its 2011 Operational Energy Strategy, which, laid down the overall guidelines for armed forces to pursue in respect of energy. The US Military has set up the goals of reduction in energy consumption, enhancing energy efficiency across platforms, enhancing usage of renewable/ alternative energy supplies and assuring energy sufficiency. To meet the desired goals, DOD has to look at deploying clean low carbon technologies at its establishments as well as increased renewable energy generation through solar, waste to energy, wind power, geothermal and other sources. In addition the DOD has to comply with a number of energy policies and executive orders that govern the DOD, these include:

-The National Energy Conservation Policy Act, 1978. It lays the foundation for energy management by US agencies.

– The Energy Policy Act of 2005. It laid down requirements and authorizations for:

-Metering of suitable federal buildings by the beginning of fiscal 2012.

– Energy-efficient product procurement.

-Use of energy saving performance contracts through fiscal 2016.

-Federal building standards that exceed by at least 30 percent industry standards set by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers.

-Renewable electricity consumption for federal agencies to increase to at least 3 percent of facility electricity consumption for fiscal 2007-09; 5 percent for fiscal 2010-12; and 7.5 percent thereafter.

-Energy Independence and Security Act of 2007. It amended the National Energy Conservation Policy Act to require agencies to improve energy intensity. It expanded authority to facilitate use of energy saving performance contracts.

-National Defense Authorization Act 2007. It codified US DOD’s goal of securing 25 percent of its energy from renewable resources by 2025.

In addition to the above, executive orders issued by the president of the United States that are applicable to US DOD energy efforts include:

-Executive Order 13423, Jan 24, 2007, requires federal agencies to, reduce energy intensity 3 percent annually, and ensure that at least half the renewable energy requirement established in the Energy Policy Act of 2005 comes from new energy sources.

-Executive Order 13514, Oct. 5, 2009, requires federal agencies to, establish a senior sustainability officer, and submit an annual Strategic Sustainability Performance Plan to the Council on Environmental Quality between fiscal 2011 and fiscal 2021. Further, it is to be ensured that new federal buildings designed in 2020 or later are ‘net zero for energy’ by 2030.

The US Army has decided to have five installations meet net-zero energy goals by 2020 and have 25 establishments achieve net-zero energy by 2030. To cut fossil fuel Army is increasingly deploying hybrid and electric vehicles.

The US Navy has set the goals of energy efficient acquisitions, sailing the Great Green fleet by 2016, reducing the non-tactical petroleum use by 50 % by 2015, producing 50% of shore based energy from alternate sources, making 50 % installations net-zero by 2020, and lastly, ensuring that by 2020, 50% of its total energy requirements would be met from alternate energy sources.

The Great Green Fleet Initiative of the US Navy. The Great Green Fleet is a demonstrator of the strategic and tactical viability of bio fuels. A strike group has embarked on a yearlong deployment in West Pacific in January 2016. The strike group (JCSSG) consists of USS John C. Stennis with Carrier Air Wing (CVW-9) and Destroyer Squadron (DESRON) 21 embarked, guided-missile cruiser Mobile Bay and guided missile destroyers Chung-Hoon, Stockdale, and William P. Lawrence. CVW-9 consists of Helicopter Maritime Strike Squadron (HSM) 71; Helicopter Sea Combat Squadron (HSC) 14; Airborne Early Warning Squadron (VAW) 112; Electronic Attack Squadron (VAQ) 133; Fleet Logistics Combat Support Squadron (VRC) 30, Detachment 4 and Strike Fighter Squadrons (VFA) 151, 97, 41 and 14[6]. The JCSSG is using alternate fuel (10 percent beef tallow and 90 percent marine diesel) and incorporating energy conservation measures. The Great Green Fleet initiative also includes use of energy efficient systems and operating procedures like changing of lights to solid-state lighting, temperature control initiative, installation of stern flaps to reduce drag etc.

The US Air Force has decided to reduce overall energy demands, increase energy supply through alternate/ renewable energy sources, and meet the “End State Goals” of DOD by 2030. These include, that bases meet Air Force energy security criteria while optimizing the mix of on‐base and off‐base generation, that aircraft fly on alternative fuel blends, that Forward Operating Bases be capable of operating on renewable energy & optimizing energy utilization. It is also testing different “Hydro treated Renewable Jet” (HRJ) fuels which comprise of bio-fuels and jet fuels in order to have 50% of its aviation fuel from alternative blends by 2016. In addition, the US Air Force is seeking to have better energy efficiency engines for its aircraft in future.

In July this year, the US Army and Air Force have come together to change all their sources of electricity to clean and renewable energy. As per Air Force News Service “The Army and Air Force have identified energy resilience as a critical objective, advancing the capability for their systems… to respond to… unexpected disruptions,” …”Now, both offices will share support staff, business processes, and best practices.”[7]

Indian Armed Forces

In order to reduce the carbon footprint of the Indian Defence Forces and associated establishments the Government of India has initiated considerable efforts under phase-II/III of the Jawaharlal Nehru National Solar Mission JNNSM. It includes setting up over 300 MW of Grid-Connected Solar PV Power Projects by Defence Establishments under Ministry of Defence and Para Military Forces with Viability Gap Funding under JNNSM. As per the annual report of Ministry of New and Renewable Energy (MNRE) for the year 2014-2015[8], some of the salient features of the scheme include:

-A capacity of 300 MW to be set up in various Establishments of Ministry of Defence with the minimum size of the project to be one MW. The defence establishments would identify locations for developing solar projects, anywhere in the country including border areas from time to time. The projects under this Scheme will mandatorily use solar cells/modules, which are made in India. The Defence organizations/Establishments will be free to own the power projects i.e. get an Engineering, Procurement, Construction (EPC) contractor to build the project for them or get a developer who makes the investment and supplies power at a fixed tariff of Rs.5.50 per unit for 25 years. The MoD or the Defence Organization would be free to follow their own procurement systems or develop detailed guidelines or procedures for tendering.

-Inter-Ministerial group has recommended National Clean Energy Fund (NCEF) Support of Rs. 750 cr.

Indian Army’s quest for green fuels has led to research into algal biomass, which is considered to be one of the best emerging sources of sustainable energy. The algal biomass can be conveniently cultivated in a matter of days at military detachments and used to produce bio-fuel for use in military vehicles. Nine DRDO labs are currently carrying out research on microalgae for extraction of bio fuels[9].

Indian Navy has completed two years of its Green Initiatives Program on World Environment Day in 2016. Navy has undertaken a large number of green measures to reduce its overall carbon footprint. An Energy and Environment Cell[10] at Naval Headquarters has been created to monitor the implementation of the green energy programs. The Navy has initiated efforts to go green in ship designs as well as its operations. It also carries out mass awareness drives in its dockyards, and shore establishments to sensitize the personnel to energy conservation.

The Navy has set a target of 21 MW Solar PV installation[11],  in line with the National Mission of Mega Watt to Giga Watt towards achieving 100 GW Solar PV installations by 2022. Navy has also pledged 1.5 per cent of its Works budget towards Renewable Energy generation. Navy is exploring the feasibility of exploiting Ocean Thermal Energy and Wave Energy as sources of green energy.

Moving Towards Smart Energy

In almost all developing and developed countries, electric industry is moving away from a centralized, producer-controlled network to one that is more consumer-interactive and less centralized. Smart Grid is a term for a functional system, which utilizes modern communication technologies with monitoring & control systems to make the electric grid more efficient. A more advanced grid utilizes information technology for processing data and allows utilities to perform grid operations. Smart grid systems also help consumers to use their energy needs in a better way[12]. In India for instance, the transmission losses are one of the highest in the world, in addition India grapples with unpredictable energy sources feeding the grid[13], it is therefore necessary to have a grid that is highly adaptive, in other words, a smart grid.

Some features of smart grid include[14]:

-Advanced Metering Infrastructure, AMI, it utilizes smart meters, communications networks for transmitting meter data, and management systems for receiving, storing, and processing the data.

-Grid modernization by deploying sensors, communications, and control technologies for efficient grid operations. Smart distribution technologies to help locate and identify defects, and carry out effective monitoring for the equipment.

– Transmission system modernization using digital equipment for monitoring and controlling operations throughout the transmission grid. It uses Synchrophasor technology, with phasor measurement units (PMUs) for measuring instantaneous voltage, current, and frequency.

– Virtual power plants, which allow discrete energy resources (DERs) to feed the electricity grid constantly and reliably.

-Micro grids, which are clusters of local DERs and loads connected in such a way that an operation is possible within the grid or in an independent mode.

The smart grid however, comes with its own challenges in terms of bandwidth and cyber security. Each application of the smart grid requires a combination of communication technologies for handling its own bandwidth and latency[15] needs. Currently, secure interoperable networks are being designed which would provide adequate cyber security.

The defense forces have taken a proactive approach to meet their energy requirements of the future with emphasis upon green energy initiatives and sensitivity to the conservation of the natural environment. The aspects of national security and energy security of the nation have also been carefully blended in the quest for going green. However, as the defense forces are also interdependent upon the civil power sources, the grids being designed would have to be smart enough to cater to distributed energy sources with two way power flows, smart management & generation of energy, cyber protection, band width management, and handling of variable power generated from renewable sources.

[1] House Armed Services Committee Subcommittee on Readiness (statement of Dorothy Robyn, deputy undersecretary of defense) (March 29, 2012), http://www.acq.osd.mil/ie/download/robyn_testimony_hasc%20mar292012.pdf. (Accessed 21 Jul 2016).

[2] http://www.natolibguides.info/smartenergy. (Accessed 23 Jul 2016)

[3] archive.defense.gov/pubs/2014_Quadrennial_Defense_Review.pd (Accessed 29 Jul 2016)

[4] http://www.natolibguides.info/smartenergy

[5] James T. Bartis &Lawrence Van Bibber, Alternative Fuels for Military Applications, 2011, RAND Corporation, Santa Monica.

[6] http://www.militaryspot.com/news/great-green-fleet-explained (Accessed 19 Jul 2016)

[7] http://sputniknews.com/military/20160407/1037608215/usaf-army-clean-energy-switch.html (Accessed 24 Jul 2016).

[8] http://mnre.gov.in/file-manager/annual-report/2014-2015/EN/Chapter%204/chapter_4.htm

[9] http://www.newindianexpress.com/states/tamil_nadu/Army-Goes-Green-to-Produce-Bio-fuel-for-Battle-Tanks/2016/03/16/article3329437.ece

[10] http://pib.nic.in/newsite/PrintRelease.aspx?relid=145978

[11] http://timesofindia.indiatimes.com/good-governance/centre/Indian-Navy-is-engaged-in-renewable-energy-generation/articleshow/52618824.cms

[12] US department of Energy, 2014 Smart Grid System Report, Report to Congress, August 2014.

[13] Navneet Gupta and Apurav Jain, Smart Grids in India, Renewable Energy,  – Ministry of New and Renewable Energy, August 2011.http://mnre.gov.in/file-manager/akshay-urja/july-august-2011/EN/Smart%20Grid%20in%20India.pdf

[14] 12 ibid.

[15] Network latency is an expression of how much time it takes for a packet of data to get from one designated point to another.

 The Challenge of Military Artificial Intelligence

 (Abridged version published in SP’s Military Year Book 2017)

Intelligent machines were the focus of research work at many institutes after the WWII. In 1950, Alan Turing argued that if the machine could successfully pretend to be human to a knowledgeable observer then one certainly should consider it intelligent[i]. The credit of coining the phrase ‘Artificial Intelligence’ goes to John McCarthy in 1955. A number of scientists have defined Artificial Intelligence, (AI) in a varying manner; however, there appears to be no single definition, which has been universally accepted. All the definitions of AI are connected with human intelligence in some way, some of them are:

– “The study of mental faculties through the use of computational models”[ii].

-“The art of creating machines that perform functions requiring intelligence when performed by people”[iii].

-“A field of study that seeks to explain and emulate intelligent behavior in terms of computational processes”[iv].

– “The study of how to make computers do things at which, at the moment, people are better”[v].

– “The study of the computations that make it possible to perceive, reason, and act”[vi].

– “The branch of computer science that is concerned with the automation of intelligent behavior”[vii].

Strong AI has been defined as that moment when “humankind is in the presence of an intelligence greater than its own”[viii], and as “strong AI is reached once the computer regarded as such is conscious of its abilities”[ix].

AI imbibes knowledge from different fields like Computer Science, Mathematics, Engineering, Cognitive Science, Philosophy, and Psychology. AI embodies a wide range of intelligent search methods, techniques for obtaining clarity where uncertainties exist in data and knowledge, and various types of machine learning & representation schemes of knowledge. Its various applications include, speech recognition, natural language processing, expert systems, neural networks, intelligent robotics, gaming and 3D vision. There is a need to define machine learning and deep learning before moving on to the military applications of AI.

Machine learning. It has evolved from the study of computational learning theory, pattern recognition, and artificial intelligence. It is a subfield of computer science.[x] It has been defined in 1959 by Arthur Samuel as a “Field of study that gives computers the ability to learn without being explicitly programmed”. Machine learning relies upon utilizing algorithm constructions to perform predictive analysis on data[xi]. Machine learning tasks fall into three basic categories namely[xii]; Supervised learning is one in which the computer is presented with example inputs and their desired outputs, and the goal is to learn a general rule that maps inputs to outputs; Unsupervised learning is one where no labels are given to the learning algorithm, leaving it on its own to find structure in its input; and Reinforcement learning is one where a computer program interacts with a dynamic environment in which it must perform a certain goal.

 Deep Learning. Le Deng and Dong Yu of Microsoft have provided the following definitions for Deep Learning[xiii]:

-A class of machine learning techniques that exploit many layers of non-linear information processing for supervised or unsupervised feature extraction and transformation, and for pattern analysis and classification.

-A sub-field within machine learning that is based on algorithms for learning multiple levels of representation in order to model complex relationships among data.

-A sub-field of machine learning that is based on learning several levels of representations, corresponding to a hierarchy of features or factors or concepts, where higher-level concepts are defined from lower-level ones, and the same lower level concepts can help to define many higher-level concepts.

Some of the deep learning architectures built around neural networks are deep belief networks, deep neural networks and recurrent neural networks. The use of deep learning architectures in automatic speech recognition, bioinformatics, natural language processing, and 3D vision etc has resulted in remarkable successes.

As per Jeff Hawkins and Donna Dubinsky of Numenta, building of smart machines has involved three basic approaches. These are the Classic AI, Simple Neural Networks, and Biological Neural Networks.[xiv]

The classic AI approach involved computer programs that were based upon abilities of the human brain to solve simple problems. However, the computers required large amounts of inputs from knowledge experts to lay down the rules based upon their expertise and experience in problem solving. Thus, the classic AI systems were created specific to a problem, while they were very useful in case of problems which had been defined in detail they could not learn on their own and provide solutions to problems. They failed in comparison with general human intelligence.

When the limitations of Classic AI were encountered, scientists looked at the functioning of the human brain at the level of neurons and this resulted in Artificial Neural Networks (ANNs). The ANNs lay emphasis upon unsupervised learning from data provided to them. Thus, the Simple Neural Networks learn from data and do not require experts to lay down the rules. The Simple Neural Network is a mathematical technique that locates patterns in large, static data sets[xv]. The ANNs are a subset of machine learning techniques that processes large amount of data using statistical and mathematical techniques in addition to ANNs to provide results. ANNs have transformed into Deep Learning networks with the advent of humongous data and fast computers. Thus, Simple Neural Networks could provide solutions where Classic AI could not. However, the Simple Neural Networks too have limitations when data is dynamic or when data is limited for training.

In the Biological Neural Approach, emphasis is laid upon studying how a human brain works to cull out the properties that are required for intelligent systems. It is established that, information is represented in the brain using sparse distributed representations or SDRs. Further, it is known that memory is a sequence of patterns, behavior is essential part of learning, and that learning has to be continuous. Therefore, the building blocks of intelligent machines should be SDRs[xvi]. The biological neuron is also not as simple as conceived during the Simple Neural Network approach.

Military applications of AI can be found in almost all aspects of military from decision-making, equipment operations, sensors, weapons systems to unmanned vehicles. The military is adopting AI mainly because it results in much fewer casualties, higher efficiency, and lower costs. Intelligent robotics and unmanned vehicles for army, navy, and air force are bringing in a new revolution in standoff warfare. The war against terrorism is practically being fought with unmanned weaponized aerial vehicles in Afghanistan, Syria and Iraq. Be it air traffic control in a combat zone, which would allow manned and unmanned aircraft, weapons etc. to operate without conflict by automated routing and planning; or military decision making in fog of war; or a radar’s target identification algorithms which look at the shape of possible targets and their Doppler signatures; AI is integral to all these systems. In this article two major categories of military applications are discussed which pertain to cyber defence and military logistics.

Applications of AI in Cyber Defence

In 2009, Conficker[xvii] worm infected civil and defence establishments of many nations, for example, the UK DOD reported large-scale infection of its major computer systems including ships, submarines, and establishments of Royal Navy. The French Naval computer network ‘Intramar’ was infected, the network had to be quarantined, and air operations suspended. The German Army also reported infection of over a hundred of its computers. Conficker sought out flaws in Windows OS software and propagated by forming a botnet, it was very difficult to weed it out because it used a combination of many advanced malware techniques. It became the largest known computer worm infection by afflicting millions of computers in over 190 countries.

It s evident that the amount of data and the speeds at which processing is required in case of cyber defence is not feasible for human beings to carry it out. Conventional algorithms also cannot tackle dynamically changing data during a cyber attack. It appears that cyber defence can only be provided by real time flexible AI systems with learning capability.

The US Defence Science Board report of 2013[xviii] states that “in a perfect world, DOD operational systems would be able to tell a commander when and if they were compromised, whether the system is still usable in full or degraded mode, identify alternatives to aid the commander in completing the mission, and finally provide the ability to restore the system to a known, trusted state. Today’s technology does not allow that level of fidelity and understanding of systems.” The report brings out that, systems such as automated intrusion detection, automated patch management, status data from each network, and regular network audits are currently unavailable. As far as cyber defence is concerned in the US, it is the responsibility of the Cyber Command to “protect, monitor, analyze, detect, and respond to unauthorized activity within DOD information systems and computer networks”[xix]. The offensive cyber operations could involve both military and intelligence agencies since both computer network exploitation and computer network attacks are involved. The commander of Cyber Command is also the Director of National Security Agency, thus enabling the Cyber Command to execute computer exploitations that may result in physical destruction of military or civilian infrastructure of the adversary. Some advance research work in respect of active cyber defence has been demonstrated under various fields of AI, some successfully tested examples are:

Artificial Neural Networks- In 2012, Barman, and Khataniar studied the development of intrusion detection systems, IDSs based on neural network systems. Their experiments showed that the system they proposed has intrusion detection rates similar to other available IDSs, but it was at least ~20 times faster in detection of denial of service, DoS attacks[xx].

Intelligent Agent Applications-In 2013, Ionita et al. proposed a multi intelligent agent based approach for network intrusion detection using data mining[xxi].

Artificial Immune System (AIS) Applications- In 2014, Kumar, and Reddy developed a unique agent based intrusion detection system for wireless networks that collects information from various nodes and uses this information with evolutionary AIS to detect and prevent the intrusion via bypassing or delaying the transmission over the intrusive paths[xxii].

Genetic Algorithm and Fuzzy Sets Applications- In 2014, Padmadas et al. presented a layered genetic algorithm-based intrusion detection system for monitoring activities in a given environment to determine whether they are legitimate or malicious based on the available information resources, system integrity, and confidentiality[xxiii].

Miscellaneous AI Applications- In 2014, Barani proposed genetic algorithm (GA) and artificial immune system (AIS), GAAIS – a dynamic intrusion detection method for Mobile ad hoc Networks based on genetic algorithm and AIS. GAAIS is self-adaptable to network changes[xxiv].

From the above it can be seen that there is rapid progress in design and development of cyber defence systems utilizing AI that have direct military applications.

Applications of AI in Military Logistics

Some of the challenges being faced by militaries in both peace and war include ensuring the adequacy of maintenance and repair of sophisticated  equipment, weapons, armament and ammunition; ensuring the supportability of missions with due planning; and guaranteeing  the availability of qualified personnel to carry out the assigned tasks. AI and associated technologies have made impressive inroads in civil and military logistics to ease the cumbersome operations and procedures involved. It has now been established that AI has significantly improved the systems and processes in the logistic chain and has led to considerable savings for the military establishments. AI encompasses many innovative technologies that are being used in military; some of these are discussed in succeeding paragraphs.

-Expert systems are software programs that usually serve as intelligent advisors in specific areas of expertise. Expert system technology has percolated to all functional areas of production and logistics of the military. Logistics expert systems in areas of inventory management, transportation, warehousing, acquisition, maintenance, and production are common. Examples include, the Inventory Manager’s Assistant of US Air Force, Dues Management Advisor (DMA) of the US Navy and Logistics Planning and Requirements Simplification (LOGPARS) system of the US Army.

-Natural language systems convert languages into computer language, thus making it feasible to communicate with computers in language of choice obviating the need to master computer languages. Natural language applications are being used to provide user-friendly query capability for large databases pertaining to logistics.

-Speech recognition systems allow user to interact directly with computers thus eliminating the use of keyboards. The voice signal is digitized and compared with stored voice patterns and grammatical rules for computer to understand the voice message. For example, US Air Force Logistics Command (AFLC) is using a speech recognition system in its depot warehouses to interface with the warehouse’s automated storage module (ASM); the US Army is using speech recognition system in association with a diagnostic system for carrying out maintenance of its motor vehicles as well as in its transportation planning[xxv].

-3D vision technology allows a computer to “sense” its environment and classify the various objects in its vicinity. The US Navy is using this in its Rapid Acquisition of Manufactured Parts (RAMP) program and the US Air Force for reverse engineering parts in its maintenance facilities. 3D vision applications are of significant importance in using robotics for logistics.

-Intelligent robots incorporate a host of AI technologies to mimic specific work undertaken by human beings. Mobile robots are being increasingly utilized in activities from patrolling to investigating and neutralizing explosives[xxvi]. Mobile robotic systems are used for carrying out routine inspections of nuclear missiles. They have eliminated the need of human element from going into containment systems. The robot is remotely operated from outside the containment zone. As far as arming of robots (Lethal Autonomous Weapons) is concerned, thousands of scientists and technologists, including, Elon Musk, Stephen Hawking, and Steve Wozniak signed an open letter in 2015 asking for a ban on lethal weapons controlled by artificially intelligent machines[xxvii]. The letter states “Artificial Intelligence (AI) technology has reached a point where the deployment of such systems is—practically if not legally—feasible within years not decades, and the stakes are high: autonomous weapons have been described as the third revolution in warfare, after gunpowder and nuclear arms.”

-Neural networks are designed based upon models of the way a human brain functions. They are capable of associative recall and adaptive learning. Because of the massive processing power associated with such networks, they are being increasingly utilized in logistic applications. Eyeriss is a new microchip fabricated at MIT and funded by DARPA that has the potential to bring deep learning to a smart phone that can be carried by a soldier[xxviii].

DRDO and AI

Centre for Artificial Intelligence and Robotics (CAIR), Bengaluru and Research and Development Establishment (Engineers) R&DE(E), Pune are the main laboratories of Defence Research and Development Organisation (DRDO) in India working in the area of artificial intelligence and robotics. A family of robots that have been developed for various surveillance / reconnaissance applications include[xxix]; RoboSen mobile robot system for patrolling, reconnaissance, and surveillance. It is capable of autonomous navigation with obstacle avoidance capability and continuous video feedback; Miniature Unmanned Ground Vehicle (UGV) is a ruggedized man-portable robotic system for low-intensity conflicts; Walking robots with six and four legs for logistics support; and Wall climbing & flapping wing robots for potential usage in Low Intensity Combat (LIC) operations.

Some projects under development include[xxx]:

-AI Techniques for Net Centric Operations (AINCO) – A suite of technologies for creation of knowledge base, semantic information reception and handling, inference reasoning, and event correlation.

-Knowledge Resources And Intelligent Decision Analysis (KRIDA) – A system that aims to achieve the management of large-scale military moves using extensive knowledge base and data handling.

-INDIGIS 2D/3D – An indigenous Geographic Information System (GIS) kernel that provides platform for development of display, analysis, and decision support involving spatio-temporal data.

-S57 Viewer – for viewing more than one lakh tracks.

-IVP_NCO and IP Lib – A comprehensive suite of image and video processing applications to provide a unified solution to image and video processing in the net-centric operations.

-Indigenous Network Management System (INMS) – An indigenous NMS with resource planning, network planning, and network monitoring tools for IP network management.

Future of Military Artificial Intelligence

The global defence sector has seen unprecedented adoption of unmanned systems and robotics. This has been mainly due to various factors like; reduction in own casualties and feasibility of riskier missions using robots; high precision, minimal collateral damage, longer endurance and range; quicker reaction times with greater flexibility; and finally cost benefits accruing due to reduction in cost of technology with increased percolation. Unmanned aerial systems comprise as much as over 80% of all military robots, in past six years US spending on military UAVs has increased by ten times[xxxi]. Today over 90 countries are operating drones with over 30 armed drone programs. Many programs including, Drone mother ships in air and water; swarm warfare on land, sea and air; high definition real time ISR; wearable electronic packages for soldiers with exoskeletons; and exotic weapon systems are likely to be inducted within the coming decade. The threat of cyber attacks on the AI systems is very real. AI Machines are connected to the human controllers for taking and executing critical commands, the linkages can be hacked both through electronic warfare as well as cyber attacks. Since AI runs entirely on software, there is a finite probability of it being manipulated and used against the owner. DARPA had run a three year ‘Cyber Grand Challenge’[xxxii] to accelerate the development of advanced, autonomous systems that can detect, evaluate, and patch software vulnerabilities before adversaries have a chance to exploit them. The competition which ended on 4th of Aug 2016, achieved its aim to prove the principle that machine-speed, scalable cyber defense is possible. This would mark the beginning of a new era in much needed cyber defence of AI systems.

 As far as AI is concerned it suffices to quote US deputy secretary of defense, Robert Work  “…the 2017 fiscal budget request will likely ask for $12-$15bn for war gaming, experimentation and demonstrations to test out the military’s theories on AI and robotics ‘in human-machine collaboration combat teaming’…”[xxxiii]

[i] http://www-formal.stanford.edu/jmc/whatisai/node1.html

[ii] Charniak, E., & McDermott, D. Introduction to artificial intelligence. Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA ©1985,ISBN:0-201-11945-5

[iii] Kurzweil, R. (The Age of Intelligent Machines. MIT Press, Cambridge, Massachusetts

[iv] Schalkoff, R. I. Artificial Intelligence: An Engineering Approach .McGraw-Hill, New York.

[v] Rich, E., and Knight, K. Artificial Intelligence. McGraw-Hill, New York, second edition.

[vi] Winston, P.H. Artificial Intelligence. Addison-Wesley, Reading, Massachusetts, third edition.

[vii] Luger, G.F. and Stubblefield, W.A. Artificial Intelligence: Structures and Strategies for Complex

Problem Solving. Benjamin/Cummings. Redwood City, California, second edition.

[viii] Barrat, James. Our Final Invention: Artificial Intelligence and the End of the Human Era. New York, NY: St. Martin’s Press.

[ix] Russell, Stuart, and Peter Norvig. Artificial Intelligence: A Modern Approach. Montreal, QC: Prentice Hall.

[x] http://www.britannica.com/EBchecked/topic/1116194/machine-learning

[xi] Ron Kohavi; Foster Provost (1998). “Glossary of terms”Machine Learning30: 271–274.

[xii] Russell, StuartNorvig, Peter  . Artificial Intelligence: A Modern Approach (2nd ed.). Prentice Hall. ISBN 978-0137903955.

[xiii] Li Deng and Dong Yu, Deep Learning: Methods and Applications. https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/DeepLearning-NowPublishing-Vol7-SIG-039.pdf

[xiv]Jeff Hawkins & Donna Dubinsky, What Is Machine Intelligence Vs. Machine Learning Vs. Deep Learning Vs. Artificial Intelligence (AI)? http://numenta.com/blog/machine-intelligence-machine-learning-deep-learning-artificial-intelligence.html

[xv] Ibid.

[xvi] Ibid.

[xvii] http://en.wikipedia.org/wiki/Conficker

[xviii] Office of the Under Secretary of Defense for Acquisition, Technology and Logistics, Resilient Military Systems and the Advanced Cyber Threat, United States Department of Defense, Defense Science Board, January 2013

[xix] U.S. Government Accountability Office, “Defense Department Cyber Efforts,” May 2011, 2–3, http://www.gao.gov/new.items/d1175.pdf.

[xx] D. K. Barman, G. Khataniar, “Design Of Intrusion Detection System Based On Artificial Neural Network And Application Of Rough Set”, International Journal of Computer Science and Communication Networks, Vol. 2, No. 4, pp. 548-552

[xxi] I. Ionita, L. Ionita, “An agent-based approach for building an intrusion detection system,” 12th International Conference on Networking in Education and Research (RoEduNet), pp.1-6.

[xxii] G.V.P. Kumar, D.K. Reddy, “An Agent Based Intrusion Detection System for Wireless Network with Artificial Immune System (AIS) and Negative Clone Selection,” International Conference on Electronic Systems, Signal Processing and Computing Technologies (ICESC), pp. 429-433.

[xxiii] M. Padmadas, N. Krishnan, J. Kanchana, M. Karthikeyan, “Layered approach for intrusion detection systems based genetic algorithm,” IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), pp.1-4.

[xxiv] F. Barani, “A hybrid approach for dynamic intrusion detection in ad hoc networks using genetic algorithm and artificial immune system,” Iranian Conference on Intelligent Systems (ICIS), pp.1 6.

[xxv] Bates, Madeleine; Ellard, Dan; Peterson, Pat; Shaked, Varda. http://www.aclweb.org/anthology/H91-1040

[xxvi] http://www.robotics.org/content-detail.cfm/Industrial-Robotics-Industry-Insights/Robotics-in-Security-and-Military-Applications/content_id/3112

[xxvii] https://www.technologyreview.com/s/539876/military-robots-armed-but-how-dangerous

[xxviii] http://www.defenseone.com/technology/2016/02/new-microchip-could-increase-military-intelligence-powers-exponentially/125715/

[xxix] http://pib.nic.in/newsite/PrintRelease.aspx?relid=124000

[xxx] http://www.drdo.gov.in/drdo/labs/CAIR/English/index.jsp?pg=Products.jsp

[xxxi] http://about.bankofamerica.com/assets/davos-2016/PDFs/robotic-revolution.pdf

[xxxii] http://www.darpa.mil/news-events/2016-08-04

[xxxiii] http://ftalphaville.ft.com/2015/12/15/2147846/the-future-military-artificial-intelligence-complex/

74. Weaponised Unmanned Vehicles in the Indian Navy: Technology Outlook

(Published IndraStra Global   May 22, 2016 )

In the Navy unmanned vehicles constitute four types of vehicles which operate in aerial, surface-land, surface-sea and underwater environments. Even though more glamorous terms like ‘autonomous vehicles’ are used to describe them, in reality, all these vehicles fall in the category of remotely controlled/piloted robotic vehicles. However, it is also true that in most of these categories, higher and higher degree of autonomous functioning can be built-in with the available technology.

The question that arises before the Indian Navy is whether it is ready to go for development of autonomous unmanned systems, which would be cable of engaging a target and inflicting lethal damage on their own? Is the Indian Navy willing to develop technologies that empower the vehicle with embedded artificial intelligence to make the final decision to launch weapons at the target independent of any human intervention?

It may be worthwhile to look at some innovative technologies, which are going to have a profound effect upon weaponised unmanned vehicles of tomorrow.

Cutting-Edge Artificial Intelligence (AI):

Whereas artificial intelligence would enable an unmanned vehicle to perceive and respond to its changing environment, the cutting edge AI would enable the unmanned vehicle to learn automatically by assimilating large volumes of environmental and tactical information. There is a need for the Indian Navy to look in to technologies and software formulations which  would permit an unmanned vehicle, for example, to launch itself, proceed to learn acoustic, magnetic or electromagnetic signatures and identify the target on its own (as distinct from current weapons like mines, torpedoes and missiles which have a tested and tried inbuilt code). The need to pursue technologies that would enable it to go a step further by taking a decision to launch its weapons could be looked at  in future.

Profound/ Deep Learning in respect of Unmanned Vehicles:

There is a definite need to look into Profound or / Deep learning technological issues since for most of the areas of their operations, unmanned vehicles would be required to accumulate vast amounts of data/ intelligence inputs from the surroundings, process it and upload it to systems for decision making by humans. Fundamentally, advanced algorithms need to be developed for unmanned vehicles through which the vehicle on its own can differentiate changes from the normal that need to be highlighted for predicting a future course of events by the analysts. Since Unmanned underwater vehicles would operational for periods extending over months at a time,one area of importance could be to make the vehicle unlearn (specific areas it has self-written the codes for), since it occupies memory space or it may no longer remain relevant.

Green Technologies for Unmanned Vehicles:

As the Unmanned systems race to achieve higher and higher levels of autonomous operations, there is a need to look into technologies, which would make unmanned vehicles more environmental friendly, like the use of green plastics of the poly hexahydrotriazines or PHTs category, which provide the same strength but are biodegradable. Similar advances need to be explored for providing the unmanned vehicles with green electrical power and its storage for long endurance operations.  Neuromorphic Technology.  Neuromorphic chips are designed to process information by mimicking human brain’s architecture resulting in massive computing and processing power. These combine data storage and data processing components in same interconnected modules thus providing power as well as energy efficiency.

Communications Pathways:

Satellites are not the only pathway for reliable communications, be it for data, voice, or command & control. There is a requirement for a resilient architecture that can act as a redundant pathway to atmospheric communications (including underwater) through electromagnetic domains including digital communications utilizing fiber domain. Fiber carries far larger bandwidth than what can be carried through the satellite systems. Multiple pathways would provide greater safety and protection to the cyber networks. Technologies need to be developed, to make the network physically resilient to deal with High Altitude Electromagnetic Pulse (HEMP), and to make the network react by itself to tampering by external actors.

Additive Manufacturing Technology:

Distributed manufacturing enables efficient use of resources, with less wasted capacity in centralized factories. It also reduces the amount of capital required to build the first prototypes and products. Further, it limits the overall environmental impact of manufacturing since digital information is transferred over the internet with local sourcing of raw materials. However, Additive manufacturing poses a potentially disruptive challenge to conventional processes and supply chains. Its nascent applications in aerospace sectors need to be developed for the unmanned systems across the Naval unmanned requirement. There is a need to examine and develop 3D printing of circuit boards and other integrated electronic components. Currently, Nano scale component integration into 3D printing is a formidable challenge for this technology. Taking a step further, adaptive-additive technologies (4D printing) would be ushering in products that would be responsive to the natural environment (like temperature and humidity) around them.

Test and evaluations of Unmanned Systems:

Test and evaluation of collaborative (Humans and robotic) systems is a big technological leap that needs to be addressed at the earliest. As of now, there is no software, which can test a collaborative system both physically, and intellectually, once an unmanned system has been tasked to learn on its own, it should have the capability to convey the extent of its learning as it progresses in its knowledge acquisition process. Navy needs to delve into cognitive testing aspects of software for unmanned vehicles today to fruitfully operate autonomous vehicles of tomorrow.

Disruptive Unmanned Warfare:

Autonomous vehicles have ushered in a paradigm shift from the few big, expensive, and lethal weapons to large numbers of small, cheap, and smart unmanned systems capable of swarming the adversary. The unmanned vehicles today can carry significant amounts of weapons utilizing new designs of weapons with nano materials. The Navy needs to explore technologies for developing new types of weapons for use in the autonomous vehicles.

Finally, the Indian Navy has to focus in the coming years on the technology developments in the commercial sector which have outpaced the developments in the military; especially in the software; and the artificial intelligence sector. It has to seek ways and means to synergize the commercial sector developments such that it can become a force multiplier ushering in the next RMA.