• College of Computer and Information Sciences. Computational Analysis of Terrorist Groups: Lashkar-e-Taiba. By: V. S. Subrahmanian. Additional. Buy Computational Analysis of Terrorist Groups: Lashkar-E-Taiba at Walmart. com. The group has instigated terrorist attacks in Kashmir and Executive Summary: Lashkar-e-Taiba (LeT), meaning “Army of the Pure,” is a violent Islamist .. et al., Indian Mujahideen: Computational Analysis and Public Policy.
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Presented at an international symposium on Lashkar-e-Taiba held in Washington on Sep 10,the study also confirms traditional wisdom that pressuring Pakistan to rein in its terrorist proxies and disrupt LeT terrorist training camps is also necessary to reduce the scope of LeT attacks. The study also is being published as a book: Besides killing hundreds of civilians, LeT threatens the stability of South Asia because its attacks heighten tensions between nuclear-armed rivals India and Pakistan.
Further, since the assault on Mumbai, information on Lashkar-e-Taiba suggests that it has increasingly turned its attention towards attacking the West not only in Afghanistan but also in Europe and Australia. Companies like Google and Amazon use these kinds of analytic methodologies to model the behaviors of customers every day.
Decision-makers dealing with deadly threats to national security should have the same kinds of tools available. The UMD researchers mined this data for temporal probabilistic rules that not only identify conditions under which different types of terror strikes are carried out by LeT or its affiliates, but also the time delay with which these actions occur.
Given these rules about the likelihood of LeT actions, a new Policy Computation Algorithm identifies sets of actions that reduce the likelihood of LeT attacks. A typical rule states that two months after Lashkar-e-Taiba operatives were arrested and Lashkar-e-Taiba operatives were on trial in either India or Pakistan, there was an 88 percent probability of Lashkar-e-Taiba engaging in clashes with local security forces in which Lashkar-e-Taiba operatives are killed.
Other rules had more nuanced implications. For example, the killing of Lashkar-e-Taiba commanders is often followed by the increased likelihood of attacks on civilians but fewer cases of other attacks.
The study found that policy-makers must continue to identify methods of pressuring Pakistan to stop supporting Lashkar-e-Taiba as its proxy against India.
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But, since this has proved difficult to do in practice, counter-terror agencies should also seek methods of sowing internal dissent within Lashkar-e-Taiba, a strategy that has been used successfully against other terrorist organizations.
Former Director of Central Intelligence, R. The authors of the study, xomputational was carried out at the University of Maryland, are V. I enjoyed the article. However I think it authors don’t have it quite right.
Computational Analysis of Terrorist Groups: Lashkar-e-Taiba | UMIACS
Yes it can figure the probabilities, probably courses of action etc. And though it makes places like Google a lot of money analysis helps in any kinds of gambling, like business it think will fail when it comes to a catastrophic event, major terrorist attack or un expected invasion etc. Kinda like the movie Lashkra-e-taiba Games. Good intel, with excellent analysis, provided to solid politicians and military leaders, isn’t going to stop, fix or solve everything.
You can’t predict the future.
But you can blame the machine. Though I am second to none in my skepticism of high tech tron slinging, this article impressed me.
Computational Analysis of Terrorist Groups: Lashkar-e-Taiba
The problem with it is the language it uses. What the heck does “temporal probabilistic rules” mean? They are talking about figuring out what people are likely to do in the future and learning how to affect their behavior, based upon what they’ve done in the past.
The difference is the computer tech allows you to have much more good knowledge abalysis what they have done in the past, if you have the right kind of programs to sift through that behavior.
Google and Amazon have those programs. All you have to do is look at how much money they make. It appears that the U of MD had the inspiration to apply those programs and methods in a compuational area. It is a great idea. I just wish they would explain clearly without the jargon. Nobody will know they have a good idea because most will stop reading right after they get hit with “sophisticated data mining algorithms to learn temporal probabilistic rules”.
It sounds as though it might be a somewhat useful tool