Big Data, a Professor and the Terrorists – The Lashkar-e-Toiba Case Study

It is highly unlikely that you have a World renowned Computer Science Professor talking about the World’s deadliest Terror Groups. But, when that unreal ambiguity presented itself, yours truly picked it up. Yes, it was a Talk organized by Aspen Institute India in New Delhi. The nature of the talk was unusual even by Aspen’s scope, a fact supported by the session moderator, Mr S Ramadorai – Advisor to the Prime Minister of India. You must be wondering about the Professor. Well here he is – V S Subrahmanian. The topic of the talk was – “Using IT to Fight Terrorism and Increase Security” to look at these questions – How can IT methods be used to come up with policies that can reduce expected intensity of terrorist attacks? In what way does the analysis of terrorist networks and video surveillance analytics lead to promising research results? Professor VS did a remarkable job in the hour long talk and Q&A session by lucidly explaining his complex projects. The two Big Data case studies that he presented were in the context:

a) Lashkar-e-Toiba (LeT)

b) IED Weapons caches in Baghdad.

The following are some key takeaways from the talk mostly in the context of the Lashkar-e-Toiba (LeT).

#1) Methodology of the Study

The method is similar to how e-commerce companies use online customer behaviors to present them with a customized experience. Similarly, here open source data from press reports was fed into the algorithm to identify the relation between open source data and low/high impact attacks by the Lashkar (LeT).

#2) Variables and Rules

Key to predicting Future attacks

This study comprised of over 770 variables captured on a monthly basis for almost the entire twenty years existence of the LeT. Basis these variables, Rules were postulated on the supposed terrorist actions by the Lashkar (LeT).

#3) Inputs to Government Policy and Counter

Terrorism Measures

Open source and social media Big Data analysis could provide valuable insights in firming up policy actions. It is possible to put forth to a reasonable degree which policy measures would have NIL or marginal effect. Such insights could help decision-making.

#4) Challenges

Data Accuracy and Predicting the Future

The analysis isn’t perfect. The more the data, the better the analysis and more the confidence in the predictions. Well that is a story, BIG Data lives with.Lastly, while the questions and answers were all over the place, the audience did POP this question – When is the next terror strike?

Professor VS did oblige and looking into the Big Data crystal ball said, – “No high impact attacks, but a few low impact attacks in the first quarter of 2013”. And that was enough caution to make an exit into the cold Delhi evening.

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