COMPUTATIONAL ANALYSIS OF TERRORIST GROUPS LASHKAR-E-TAIBA PDF

It succeeds in measuring, in objective terms, the degree of cybersecurity vulnerabilities of different states and compares them scientifically. Subrahmanian have produced a fascinating framework for a disciplined analysis of terrorist groups As a former Director of National Intelligence, I know this book will be an invaluable asset to counter-terrorism analysts and policymakers. It is a must read. Understanding it requires creative thinking and analysis of exactly the sort VS Subrahmanian and Aaron Mannes offer in this important contribution to the growing Lashkar canon. Highly recommended for policymakers, practitioners and anyone interested knowing more about the South Asian region or transnational terrorism.

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Computational Analysis of Terrorist Groups: Lashkar-e-Taiba provides an in-depth look at Web intelligence, and how advanced mathematics and modern computing technology can influence the insights we have on terrorist groups. This book primarily focuses on one famous terrorist group known as Lashkar-e-Taiba or LeT , and how it operates. After 10 years of counter Al Qaeda operations, LeT is considered by many in the counter-terrorism community to be an even greater threat to the US and world peace than Al Qaeda.

This book presents how to quantify both the environment in which LeT operate, and the actions it took over a year period, and represent it as a relational database table. This table is then mined using sophisticated data mining algorithms in order to gain detailed, mathematical, computational and statistical insights into LeT and its operations.

This book also provides a detailed history of Lashkar-e-Taiba based on extensive analysis conducted by using open source information and public statements. Computational Analysis of Terrorist Groups: Lashkar-e-Taiba is designed for a professional market composed of government or military workers, researchers and computer scientists working in the web intelligence field.

Advanced-level students in computer science will also find this valuable as a reference book. Springer Professional. Back to the search result list.

Table of Contents Frontmatter Chapter 1. Introduction Abstract. This chapter contains a brief introduction to Lashkar-e-Taiba. It describes their geographic locations and also summarizes statistics about violent terror acts carried out by LeT, briefly describes the behavioral rules about LeT derived in this book, and summarizes suggested policy options generated automatically from the LeT data set. This chapter provides an overview of LeT from their creation to the end of It describes the goals of the group, other groups in their ecosystem, the types of attacks they have carried out, the internal dynamics of the group, and the relations they have with the Pakistani military and civilian government.

It also includes brief profiles of selected LeT leaders. This chapter describes the syntax and semantics of Temporal Probabilistic or TP behavioral rules used throughout the book to describe the behavior of Lashkar-e-Taiba. The chapter describes the intuition behind TP-rules, their formal syntax and meaning, and describes an algorithm used to derive the TP-rules automatically from data about LeT.

LeT has carried out numerous operations in which civilians were both the real and intended targets. This chapter focuses on the conditions under which LeT carried out attacks against civilians in general, or civilians on the basis of their religious identity primarily Hindus, but also taken broadly to include Christians and Jews. The chapter discusses several TP-rules derived automatically from the LeT data set used in this book. This chapter describes the conditions under which LeT carries out terrorist attacks against three types of targets: public sites, tourist sites, and transportation facilities such as railway stations and airports.

The chapter discusses several TP-rules about these types of terror attacks that were derived automatically from the LeT data set used in this book.

LeT has carried out numerous attacks against professional security forces—primarily the Indian Army and police. This chapter describes the conditions under which LeT carries out terrorist attacks against professional security forces.

This chapter describes the conditions under which LeT carries out terrorist attacks against security installations such as military bases, police stations, and checkpoints. This chapter describes the conditions under which LeT carries out terrorist attacks on holidays as well as attempted but unsuccessful attacks. This chapter describes the conditions under which LeT engages in armed clashes, usually with Indian local or national security forces. The chapter discusses several TP-rules about armed clashes involving LeT that were derived automatically from the LeT data set used in this book.

This chapter describes the methodology and the algorithm used to automatically compute policy options. The reason for this is that attacks on holidays are carried out in situations that are inconsistent with situations when LeT carries out other types of attacks. The chapter presents an algorithm to compute all policies in accordance with the mathematical definition of policy that have good potential to significantly reduce all types of attacks carried out by LeT except for attacks on holidays.

Readers who do not wish to wade through the technical details can skip directly to Sect. The Policy Computation Algorithm described in Chap. This chapter describes 4 of these policies in detail the other 4 are very similar. It shows that these policies are complex, involving many different actions to be taken—yet they overlap extensively in terms of what should be done and what should not be done in combating LeT terror acts.

The chapter also includes some tactics that policy makers may consider in implementing these policies. Print ISBN Electronic ISBN Authors: V.

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Computational Analysis of Terrorist Groups: Lashkar-e-Taiba

Computational Analysis of Terrorist Groups: Lashkar-e-Taiba provides an in-depth look at Web intelligence, and how advanced mathematics and modern computing technology can influence the insights we have on terrorist groups. This table is then mined using sophisticated data mining algorithms in order to gain detailed, mathematical, computational and statistical insights into LeT and its operations. Advanced-level students in computer science will also find this valuable as a reference book. Skip to main content Skip to table of contents. Advertisement Hide. This service is more advanced with JavaScript available.

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Computational Analysis of Terrorist Groups: Lashkar-e-Taiba provides an in-depth look at Web intelligence, and how advanced mathematics and modern computing technology can influence the insights we have on terrorist groups. This book primarily focuses on one famous terrorist group known as Lashkar-e-Taiba or LeT , and how it operates. After 10 years of counter Al Qaeda operations, LeT is considered by many in the counter-terrorism community to be an even greater threat to the US and world peace than Al Qaeda. This book presents how to quantify both the environment in which LeT operate, and the actions it took over a year period, and represent it as a relational database table. This table is then mined using sophisticated data mining algorithms in order to gain detailed, mathematical, computational and statistical insights into LeT and its operations.

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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. 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..

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It seems that you're in Germany. We have a dedicated site for Germany. Authors: Subrahmanian , V. Computational Analysis of Terrorist Groups: Lashkar-e-Taiba provides an in-depth look at Web intelligence, and how advanced mathematics and modern computing technology can influence the insights we have on terrorist groups. This table is then mined using sophisticated data mining algorithms in order to gain detailed, mathematical, computational and statistical insights into LeT and its operations. Advanced-level students in computer science will also find this valuable as a reference book. As a former Director of National Intelligence, I know this book will be an invaluable asset to counter-terrorism analysts and policymakers.

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