In today’s environment, information can be obtained by a variety of means. One of the means is machine data, which is generated by various means like the movement of vehicles, aircrafts, ships, unmanned aerial vehicles (UAVs), reconnaissance aircraft, battlefield surveillance radars (BFSR) and satellites in space. On the other hand, human generated data includes data from mobile phone usage and social media apps like YouTube, Facebook, Twitter, Watsapp, Instagram, etc. Business data is generated from all e-commerce transactions. All these data have intelligence, which we cannot afford to neglect.
Big data analytics finds huge importance as far as intelligence inputs are concerned. It is being utilised to continuously gather intelligence for national and military intelligence during peace and war – the quantum varies as per the requirement, ie, during crises and war. Human analysis of this data is well beyond physical capability and, therefore, big data analytics-based intelligence provides the requisite output required for decision making and conduct of operations.
Aspects Associated with Data
Big data analytics gives a big boost to intelligence gathering when there is an information deluge because of the following aspects associated with future data:
• Volume. Data is ever growing. It will grow at scale ranging from terabytes to petabytes.
• Variety. Data received from different sources is in structured, semi-structured, unstructured formats.
• Veracity. Managing the reliability and predictability of inherently imprecise data types is complex and challenging.
• Complexity. Relationships, hierarchies and multiple data linkages are required to be connected and correlated
Discovery of useful, unexpected patterns data, non-trivial extraction of implicit, previously unknown and potentially useful information from data by automatic or semi-automatic means of analysis in order to discover meaningful patterns leading to data simulation and modeling will be the order of the day as part of the Intelligence, surveillance & reconnaissance (ISR) philosophy.
Enhancing Military Intelligence
Engaging and scrutinising social media platforms can give us answers to many security incidents which otherwise may go unnoticed. Big data analytics has a potentially significant role in helping to manage the data deluge and assisting analysts in focusing their efforts. The various defence intelligence agencies in the country should build on the huge investments being made in this area by the commercial sector.
In modern combat scenarios, a data scientist helping interpret and analyse data could save many more lives than hundreds of troops on the ground. Algorithms can be developed to analyse hundreds of thousands of open-source documents generated each hour and compare them with the human intelligence gathered and billions of historical events and then have predictive capability to anticipate specific incidents and suggest measures proactively. Big data analytics can provide the following platforms as value additions:
• Threat Alert System. Alogrithms can be designed which can alert the commanders on the mention of concepts such as terrorism, bombs, riots, etc., across various information sources. Trending offensive videos/content specific to a person, organisations, geography, etc., can be undertaken.
• Social Media Monitoring. Prime topics/ concepts being discussed in the social media can be monitored and studied specific to geography, person and organisation, etc. Analytics of information source, for example, affinity of information sources to a specific user group, geography, etc, will have high intelligence value. The sentiments of people regarding a policy or concepts can be known and proactive actions taken, as required.
• Information Mining. Information in the news/documents related to a specific person, concepts, etc, can be searched to find out the posts related to a given concept. New information regarding a specific topic, for example, on missile defence – new articles, publications, white papers, patents and other information related to this topic comprise inputs that will be of great help in planning the intelligence strategy at the higher level.
• Social Network Monitoring. A study of related people based on social networks can be undertaken. Topics discussed by related people which represent information about the behaviour of a person will have very high intelligence value. Macro analysis of social media graphs to identify users’ groups active on a website can be analysed.
• Document Analytics. Concepts, topics discussed in a document collection can be studied. For example, the topics that the foreign ministry of Pakistan is focussed on, based on analysing the articles/documents on its website. The documents can be grouped into separate segments – documents discussing politics, sports, games, foreign affairs, etc. Finding trends related to specific topics might be an important way to discover the hidden insights in a document.
Perception in the Analytical Workflow
In counter-intelligence/ counter-terrorism (CI/CT) operations, big data collected by drones, satellites, UAVs, technical intercepts, etc., can be automatically analysed based on the big picture provided by ISR data, which can be created as part of the big data initiative. This will allow the CI/CT operations to be carried out in real time. Data intensive Geographic Information System (GIS)-based applications can be used with big data platforms in the hinterland to assist the forces deployed to fight left wing extremism.
Implementation Model
The military leaders of the future will not be able to cope if they cannot handle ambiguity in decision making. Missions and responsibilities coming in the way of military leaders today, were not even imagined a few decades ago. The social media platforms today are big enablers and not just mere search engines. They are a medium of communication that allows a multi-dimensional view against the earlier uni-dimensional view. Implementation should follow an evolutionary path within the wider information management/ information exploitation strategy and be coherent with the defence Information & Communication Technology (ICT) strategy. It should not rely solely on big data capabilities for the defence forces. Rather, the defence forces should build on the huge investment in this area being made by the commercial sector and in doing so, ensure that they are well positioned to track and exploit further commercial technological developments, as and when they occur.
To start with, the initial focus should be on day-to-day functional issues since this will help build up a case for the usefulness of big data. Some guidelines are as follows :-
• Prepare the defence intelligence agencies culturally to transform operations based on big data analytics through change management applied top down.
• Incorporate data analytics/data mining as a module in all the ongoing projects where better delivery can be achieved.
• Initially, use commercial off-the-shelf (COTS) software on an experimental basis and then opt for own research & development (R&D) for product development after gaining sufficient experience to translate the requirement technically.
• Technology and non-disclosure agreements on data sharing, to develop algorithms developed by industry, R&D institutes and academia on live data, which will be more realistic than development on synthetic data.
• In-house skill set development, from the data analyst to the data scientist.
• Pilot projects to validate concepts.
Indian Perspective
Army Chief General Bipin Rawat has stressed on the need to focus on incorporating Artificial Intelligence (AI) and Big Data computing in the armed forces as China was way ahead in terms of spending on this technology. The armed forces today are the repository of big data and there is a need to record, institutionalise the information and carry out predictive analysis using AI.
The Big Data applicability in defence forces is urgently required in the fields of intelligence and surveillance, border, maritime and space management, operational planning, logistics management, financial management, disaster management, cognitive analytics and analysis of archival data.
Some challenges in terms of requirement of qualified Big Data scientists, security policy related to data cleansing from legacy applications and achieving standardisation and change management issues can be overcome by following an evolutionary path of implementation which should be in synchronisation with the IT roadmap of the armed forces.
Final Word
Big data analytics is the way forward for enhance military intelligence. Intelligence gathering based on big data analytics has a potentially significant role in helping to manage the data deluge and assisting analysts in focussing their efforts. Evidence-based information superiority and fully analysed intelligence outputs will give increased situational awareness, which will be the primary requirement of commanders at all levels to fight a war of any type in the future.
Intelligence of such class, based on big data analytics, will enable commanders to assess the battlefield situation in real time and in a better way to take appropriate and timely decisions. Such a system can integrate the efforts of all intelligence gathering functionaries to optimise the resources and results. Intelligence report generation and distribution to local, national and international partners can become quick and easy. Such systems can be continuously refined in response to the changing behaviour of the target and stakeholders.
