Jana Shakarian

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 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. Computational Analysis of Terrorist Groups: Lashkar-e-Taiba is the first book that demonstrates how to use modern computational analysis techniques including methods for big data analysis. This book presents how to quantify both the environment in which LeT operate, and the actions it took over a 20-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. Each chapter includes a case study, as well as a slide describing the key results which are available on the authors web sites. 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.

A Computationally-Enabled Analysis of Lashkar-e-Taiba Attacks in Jammu and Kashmir

Lashkar-e-Taiba (LeT for short) is one of the deadliest terrorist groups in the world. With over 100 attacks worldwide since 2004, LeT has become a political force within Pakistan, a proxy militia for the Pakistani Army, and a terror group that can carry out complex, coordinated attacks such as the 2008 Mumbai attacks. We have collected 25 years of data about LeT starting in 1985 and ending in 2010. The data is recorded on a monthly basis and includes the values of approximately 770 variables for each month. The variables fall into two categories -- action variables describing actions taken by LeT during a given month and environmental variables describing the state of the environment in which LeT was functioning. Based on this data, we have used our Stochastic Opponent Modelling Agent (SOMA) platform to automatically learn models of LeTs behavior. These models describe conditions under which LeT took various actions -- more importantly, the conditions act as predictors of when they will take similar actions in the future. In this paper, we focus on attacks by LeT in Jammu & Kashmir. We describe some conditions under which LeT ramps up offensive activities in Jammu & Kashmir. We conclude with some policy options that may reduce the use of violence by LeT as indicated by the rules presented here.

Automated Coding of Decision Support Variables

With the enormous amount of textual information now available online, there is an increasing demand – especially in the national security community – for tools capable of automatically extracting certain types of information from massive amounts of raw data. In the last several years, ad-hoc Information Extraction (IE) systems have been developed to help address this need [6]. However, there are applications where the types of questions that need to be answered are far more complex than those that traditional IE systems can handle, and require to integrate information from several sources. For instance, political scientists need to monitor political organizations and conflicts, while defense and security analysts need to monitor terrorist groups. Typically, political scientists and analysts define a long list of variables – referred to as “codebook” – that they want to monitor over time for a number of groups. Currently, in most such efforts, the task of finding the right value for each variable – denoted as “coding” – is performed manually by human coders, and is extremely time consuming. Thus, the need for automation is enormous.

A Brief History of LeT

This chapter provides an overview of LeT from their creation to the end of 2011. 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.

Other Types of Attacks

This chapter describes the conditions under which LeT carries out terrorist attacks on holidays as well as attempted (but unsuccessful) attacks. 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.

Attacks Against Public Sites, Tourist Sites and Transportation Facilities

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.

Attacks Against Security Installations and Infrastructure

This chapter describes the conditions under which LeT carries out terrorist attacks against security installations such as military bases, police stations, and checkpoints. 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.

Policy Options Against LeT

The Policy Computation Algorithm described in Chap. 10 was used to generate a total of 8 policies that have a reasonable chance of reducing most types of LeT backed attacks. 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.

Attacks Against Professional Security Forces

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. 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.