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Lashkar-e-Taiba Attacks in Jammu & Kashmir A. Mannes2,3, J. Shakarian2, A. Sliva1,2,3,4 and V.S. Subrahmanian1,2 2Institute for Advanced Computer Studies & 3School of Public Policy 4 Northeastern University, Boston, MA 02115.
Abstract—Lashkar-e-Taiba (LeT for short) is one of the deadli- a much larger number—over 2,000—of such rules) using est terrorist groups in the world. With over 100 attacks worldwide the SOMA rule extraction engine. Here we will study the since 2004, LeT has become a political force within Pakistan, a proxy militia for the Pakistani Army, and a terror group that cancarry out complex, coordinated attacks such as the 2008 Mumbai 1) Armed clashes with Indian Security Forces in J & K that attacks. We have collected 25 years of data about LeT starting in lead to casualties on the latter’s side; 1985 and ending in 2010. The data is recorded on a monthly basis 2) Armed clashes with Indian Security Forces in J & K that and includes the values of approximately 770 variables for each month. The variables fall into two categories—action variables 3) Attempts to target security infrastructure in J & K; describing actions taken by LeT during a given month andenvironmental variables describing the state of the environment 4) Specific attempts to target civilians in J & K on the basis in which LeT was functioning. Based on this data, we have of ethnicity (i.e., civilian Hindu targets); used our Stochastic Opponent Modelling Agent (SOMA) platform 5) Murders (hits) on civilians in J & K when they are to automatically learn models of LeT’s behavior. These models describe conditions under which LeT took various actions—more 6) Use of fedayeen (suicide) attackers in J & K.
importantly, the conditions act as predictors of when they willtake similar actions in the future. In this paper, we focus on Thus, a number of the rules we have derived specify conditions attacks by LeT: those relating to attacks by LeT in Jammu & when LeT executes attacks on Indian security forces that Kashmir1. We describe some conditions under which LeT ramps lead to casualties on the Indian side. We will describe these up offensive activities in Jammu & Kashmir. We conclude with rules in some detail, together with the probability calculations some policy options that may reduce the use of violence by LeTas indicated by the rules presented here.
that explain why these rules are compelling. We also derivepotential policies to rein in LeT on the basis of these rules.
One of the world’s deadliest terrorist groups, Lashkar-e- The data used for this analysis of LeT’s behavior is part of Taiba (LeT) has carried out 100 attacks worldwide since 2004, the Computational Modeling of Terrorism (CMOT) project, killing over 700 people (according to the US National Counter- which is a specialized codebook for developing datasets Terrorism Center’s Worldwide Incident Tracking System [1]), on terrorist and other violent organizations throughout the LeT has become a political force within Pakistan, a proxy world. In addition to LeT, we have collected data for Jaish- militia for the Pakistani Army, and a terror group that can carry e-Mohammed (JeM), Indian Mujahideen (Mujahideen fi-al out complex, coordinated attacks such as the 2008 Mumbai Hind), Students Islamic Movement of India, Forces Democra- attacks. In this paper, we describe our computational study tique de Liberation du Rwanda (FDLR), and many others.
of conditions under which LeT has taken various offensive The CMOT data is an example of a behavioral time series actions in the past in Jammu & Kashmir (J & K) and use this dataset, a class of relational time series databases that can be behavioral model for predictive purposes, presenting several used to describe the context and behavior of an agent or group.
policies that might diminish LeT’s activities in J & K.
We assume the existence of some arbitrary universe A whose We start in Section II by describing the data we have elements are called attribute names (attributes for short).
collected on LeT and how this data is structured. Then, in Each attribute Att has an associated domain dom(Att). In Section III, we describe our Stochastic Opponent Modeling these datasets, the attributes fall broadly into two categories— Agents (SOMA) platform and how we extracted rules about environmental (independent) attributes describing the context LeT’s behavior from the data. Section IV provides a detailed in which a group functioned during a given time frame, analysis of about 18 interesting rules we have extracted (of and action (dependent) attributes describing actions taken by 1Actions relating to other kinds of LeT operations in the rest of India and the group. A table in the CMOT dataset for a particular Pakistan will not be considered in this paper.
terror group consists of a schema {E1, . . . , En, A1, . . . , An} of attibutes in A, where each Ei is an environmental attribute where B is an action atom and B1, . . . , Bk are all environ- describing the context of the group and each Aj is an action mental atoms. Intuitively, this rule says that if the probability attribute describing the group’s behavior.
of environmental atom B1 is in the interval [ 1, u1] and the Environmental attributes in CMOT include (i) the group’s probability of environmental atom B2 is in the interval [ 2, u2] ideological goals (i.e., religious rule of a region, territorial and so forth, then the probability of the group (LeT in the case autonomy, etc.), (ii) the political, economic, cultural, and of this paper) carrying out action B is in the interval [ , u].
security context of the state in which the group is active (i.e., A SOMA-rule is conditional iff 1, u1, . . . , n, un are all 1.
diplomatic relations, the inflation rate, ethnic tensions, etc.), In this case, the above SOMA-rule has the simplified form: (iii) the equipment and weapons possessed or acquired by thegroup, (iv) basic characteristics of the group (i.e., leadership structure, membership base, etc.), and (v) the relationships [4] provides an algorithm to automatically extract SOMA- of the group with third paries (i.e., financial backing from rules from behavioral time series datasets such as those a diaspora, military support from a foreign state, etc.). Action described in Section II. Though a detailed discussion of this attributes describe the behaviors and communications engaged algorithm is beyond the scope of this paper, we note briefly in by the group, such as specific types of attacks (e.g., bomb- that for an action attribute A, our algorithm finds logical ings, abductions, assassinations), targets (security personnel, conjunctions B1 & . . . & Bn of environmental atoms such that: civilians), and propaganda, as well as statistics regarding theoutcomes of these events, such as deaths or casualties.
• Precision. P(A|B1 & . . . & Bn) > τ where τ is a thresh- old parameter. According to this condition, any SOMA- For each time period in the dataset, experts in political rule should be true a sufficient percentage (τ %) of times.
science, anthropology, public policy, and terrorism studies,researched the behavior and context of the organization using • Support. The number of months in which the environ- open source news articles and scholarly publications. The data 1 & . . . & Bn was true exceeds a threshold set by us (i.e., the precondition of the rule for LeT has been coded at a monthly granularity from January should be true at least some fixed number of times).
1985 to December 2010. Because LeT is active across a broadregion, distinct datasets were created for LeT in Pakistan, • Spread. P(A|B1 & . . . & Bn) − P(A|¬(B1 & . . . & Bn)) exceeds a given threshold. This says that the probabil- India, J & K, Bangladesh, and Afghanistan. In this paper, we study LeT’s behavior and environment in Pakistan and J & K.
is significantly higher than the probability of A being true, given that (B1 & . . . & Bn) is not true. The larger the difference of these two probabilities, the better thecondition (B1 & . . . & Bn) distinguishes between when Stochastic Opponent Modeling Agents (SOMA) are a the group takes action A versus when they do not.
paradigm introduced in [2], [3], [4] to model the behaviorof many entities, including terrorist groups. As virtually all The algorithm can support additional statistical tests spec- attempts to predict behaviors are uncertain, SOMA models ified by the user. Using this algorithm, we extracted a total are a class of probabilistic logic rules.
of approximately 2000 rules governing the behavior of LeT.
As mentioned in Section II, our data about LeT is stored in a Below we discuss a sample of these rules related to violent acts carried out by LeT in J & K.
where each Ei is an environmental attribute and each Aj is an IV. SOMA RULES ON LET ACTIONS IN JAMMU & action attribute. Each of these attributes acts like a predicate symbol and has an associated domain dom(−). We use Attto denote an arbitrary attribute in {E A. Attacks by LeT on Indian Security Forces in J & K An environmental (resp. action) term w.r.t. attribute Att is We first study attacks by LeT on Indian security forces in either an element of dom(Att) or a variable symbol ranging Jammu & Kashmir. These attacks predominantly occur in the over dom(Att) where Att is an environmental (resp. action) summer months when mountain passes in J & K are open, other (non-weather) conditions governing when these attacks An environmental (resp. action) atom is an expression of the form Att(t) where Att is an environmental (resp. action) Rule 1. When LeT receives financial support from Pakistan’s attribute and t is a term w.r.t. Att.
diaspora and when they are engaged in business activities in Thus, in our LeT data set, the action atom fedayeen(100) Pakistan, then there is a 71.4% probability that they will carry may indicate that fedayeen attacks by the group killed out armed attacks against Indian security forces in J & K.
100 non-group individauls. Likewise, the action atom armedclashSF(10) may indicate that armed clashes between Receiving financial support from Pakistan’s diaspora.
LeT and armed security forces in J & K led to 10 deaths.
They are engaged in businesses in Pakistan.
To understand the impact of the joint occurrence of these B1 : [ 1, u1] & . . . & Bk[ k, uk] two events (C1) and (C2), we examined other probabilities: 1) As mentioned above, the probability of armed attacks by This rule indicates a high likelihood of attacks on Indian LeT on Indian security forces in J & K is 71.4% when security installations in J & K when the group is supposedly not in existence. In dissolving, LeT (usually in response to 2) However, when either (C1) or (C2) is false, the proba- international pressure) states that it no longer has an armed bility goes of these attacks goes down to 0.02%.
wing. The data collected shows the opposite. One explanation This rule indicates that armed clashes are very likely when is that when LeT explicitly claims to be a religious group, it LeT is receiving support from the Pakistani diaspora and is must show its members that it is still committed to jihad.
running business operations in Pakistan. When LeT operations Rule 4. LeT is likely to engage in armed clashes with Indian have multiple sources of income, they are more likely to be security forces in J & K involving LeT casualties when there on the attack. It is also possible that LeT steps up operations is some kind of natural disaster in Pakistan and when there is in response to diaspora support, delivering on its rhetoric.
The combination of these two methods of fund-raising— As in the previous cases, this rule has two antecedents.
running legitimate businesses and raising money from the There has been a natural disaster in Pakistan.
Pakistani diaspora—provide LeT with a more robust revenue There is internal social strife in Pakistan.
stream that allows LeT to expand its violent operations. Ryan In contrast, when either (C5) or (C6) is false, the probability Clarke [5] explains that engaging in legitimate commerce of LeT engaging in clashes with Indian security forces that gives LeT greater options to avoid international financial lead to LeT casualties drops down to just 0.02%.
sanctions. Just like organized crime syndicates, LeT engages This rule indicates a high probability of armed clashes with in legitimate businesses both to diversify its revenue sources Indian security forces in J & K in which LeT operatives are and conceal its financial activity from authorities.
killed when Pakistan is suffering from natural disasters and Rule 2. When LeT is getting financial support from their internal strife. Pakistan is frequently the victim of earthquakes Pakistani diaspora and when they are an explicit religious and storms, such as the 2005 earthquake in Kashmir that killed organization, then there is a 100% probability that they will thousands and the 2010 floods that displaced tens of thousands carry out armed attacks against Indian security forces in J & K.
and did $10 billion in damage. Pakistan is also a quilt of As in the previous case, this rule has two pre-conditions.
frequently clashing religious and ethnic identities. Religious Receiving financial support from Pakistan’s diaspora.
minorities are regularly attacked and Pakistan’s largest city, They are an explicitly religious organization.
Karachi, frequently sees fighting between its Pashtun and In contrast, when either (C1) or (C3) is false, there is only Urdu residents. Disasters can exacerbate ethnic tensions as a 0.016% probability of attacks on Indian security forces by communities vie for aid. LeT might ramp up operations during LeT, implying that both these conditions being true together these periods to emphasize Pakistan’s “national purpose.” LeT greatly increases the probability of attacks on India.
is often mentioned for its charity work, but when Pakistan This rule indicates a high probability of LeT targeting faces difficult times, the data shows that they do not reduce J & K security forces when it is a religious organization in their efforts to infiltrate Kashmir. Source: Pakistan: Minori- Pakistan and is receiving diaspora support. Diaspora support ties test aid impartiality, September 8 , 2010 IRIN, URL: is important for the resources it provides (see above) and as a http://www.irinnews.org/Report.aspx?Reportid=90422.
major religious group claiming to spearhead jihad and to raise Rule 5. When LeT is engaged in an alliance with a non-state money, LeT needs to carry out high profile operations.
armed group in J & K and there is social strife in Pakistan, there Religious appeals are central to LeT’s fundraising efforts.
is an 88.89% probability that they will attack Indian security During Eid al-Adha (Feast of the Sacrifice) when traditional forces in J & K and inflict casualties on the Indian side.
Muslims sacrifice an animal, LeT allows Pakistanis in the As in the previous cases, this rule has two preconditions.
UK to purchase a share in an animal in Pakistan and fulfilltheir religious obligation. One report states that in 2003, LeT There is internal social strife in Pakistan.
raised over $10 million through this appeal. LeT’s religious LeT has entered into an alliance with a non-state infrastructure strengthens its fundraising appeals so that LeT has greater resources for its militant cadres. Source: South When either condition (C6) or (C7) is not true, the proba- bility of LeT engaging in armed clashes with Indian security Rule 3. When LeT is officially considered a “dissolved” forces in J & K and inflicting casualties is only 0.026%.
organization, and when it is explicitly religious, then there This rule indicates high probabilities of armed clashes in is a 71.4% probability that LeT will target Indian security which Indian security forces in J & K are killed when there is social strife in Pakistan and the group has alliances with other As in the previous cases, this rule has two pre-conditions.
LeT is an explicitly religious organization.
Pakistan-backed NSAGs operating in J & K cooperate to They have officially been dissolved.
counter Indian security. In July 2009, Kashmir police arrested In contrast, when either conditions (C3) or (C4) above are two al-Badr militants who also provided SIM cards and hawala false, then there is only a 0.01% probability that Indian money transfers for LeT. When NSAG commanders are killed, security forces will be targeted in J & K.
Indian investigators usually find evidence of coordination with other groups. Some NSAGs operating in J & K, like LeT is a religious organization in J & K.
LeT, focus on the issue of national unity and ignore sectarian LeT receives military support from Pakistan.
squabbles. During times of social strife in Pakistan the jihadi In contrast, when either of these two conditions is false, organizations may increase cooperation to carry out attacks the probability of LeT carrying out fedayeen attacks in J & K that shift focus to Kashmir. Source: “2 Al-Badr Militants drops down dramatically to just 0.014%.
Arrested in Kashmir,” Fayaz Wani, July 25, 2009, URL: http: This rule indicates an increased likelihood of fedayeen //newsblaze.com/story/20090625125019kash.nb/topstory.html.
attacks when LeT receives military support from the Pakistani government and is a religious organization in J & K ˙ combination of conditions indicates a period where LeT http://www.thaindian.com/newsportal/india-news/ has increased operational capabilities. Coding as a religious lashkar-commander-killed-in-jammu-and-kashmir organization usually indicates that LeT’s networks are stronger and it has greater scope of action, while Pakistani militarysupport enables LeT to plan and launch complex operations.
Rule 8. When LeT receives support from the Pakistani military Using the SOMA rules, we also looked at the conditions and when they try to eliminat non-conformance to their ideal- under which murders are carried out in J & K by LeT.
ized beliefs in Pakistan, then there is a 70% probability of their Rule 6. When LeT is a religious organization in J & K, and carrying out fedayeen attacks in J & K.
when they have training camps in Pakistan, then there is a As in the previous cases, this rule has two preconditions.
55.55% probability that they will carry out murders in J & K.
LeT receives military support from Pakistan.
As in the previous cases, this rule has two preconditions.
(C10) LeT is advocating adherence to their belief system.
LeT is a religious organization in J & K.
In contrast, when either of these two conditions is false, the probability of LeT carrying out fedayeen attacks in J & K When one or both of these pre-conditions is false, the drops down dramatically to just 0.01%.
probability of LeT murders in J & K is about 0.016%.
One of LeTs main goals is for the Pakistani people to This rule indicates a higher likelihood of LeT committing embrace LeTs vision of pure Islam, which requires every murders in J & K when it has training camps in Pakistan and Muslim to support jihad against those oppressing Muslims [6].
it is a religious group in J & K. Murders refer to hits on From LeTs perspective, J & K is an area requiring liberation.
civilians who have crossed LeT (as opposed to massacres in This worldview fosters the conditions needed to recruit feday- which many are killed semi-anonymously, or assassinations in een attackers. Pakistani military support also plays a critical which the victim is prominent.) The two conditions indicate role. Fedayeen attackers must evade Indian security forces and periods when the LeT networks in J & K are strong and well penetrate into J & K to an appropriate target. Besides training supported. Active training camps means that LeT has cadres and equipping LeT operatives, the Pakistani military provides to move into J & K, while being a religious organization in intelligence to facilitate infiltration. After 9/11 Pakistan’s more J & K means the group has resources already in place.
overt military support for LeT decreased (although it was LeT frequently targets individuals and families in J & K.
never cut off completely) [8], reducing the successful fedayeen Individuals targeted include activists who oppose LeT and Kashmir’s Hindu minority (such as the August 2006, LeT In addition, we have derived three rules related to releases murder of three members of the only Hindu family in the of LeT prisoners by India. These rules indicate that releasing village Harra). Training camps in Pakistan and operating as LeT captives by India leads to no reciprocity of goodwill from a religious organization in J & K support goals, increasing LeT—-rather, it is correlated with fedayeen attacks.
LeT’s capability to carry out violent attacks. LeT’s religious Rule 9. When LeT is trying to rid J & K of external influences and training infrastructures also indoctrinate its members to and India has released LeT prisoners, then there is a 71.4% carry out atrocities. LeT’s rhetoric is virulently anti-Hindu.
probability that LeT will carry out fedayeen strikes in India.
At the training camps recruits undergo months of training As in the previous cases, this rule has two preconditions.
and indoctrination. [6], [7]. Source: South Asia Terrorism Por- (C11) LeT is trying to rid J & K of external influences.
tal, URL: http://www.satp.org/satporgtp/countries/india/states/ (C12) India has released LeT prisoners.
jandk/terrorist outfits/lashkar e toiba lt.htm.
In contrast, when either of these two conditions is false, the probability of LeT carrying out fedayeen attacks in J & K In LeT’s fedayeen attacks, the perpetrators storm a target drops down dramatically to just 0.03%.
and intend to die in combat, but, unlike suicide bombings, the Rule 10. When LeT is trying to ensure that Pakistanis conform attacker will not die by his own hand and may survive.
to LeT’s idealized beliefs and when India releases LeT prison- Rule 7. When LeT is a religious organization in J & K and ers, then there is a 71.4% probability that LeT will carry out receives military support from Pakistan, the probability that LeT will carry out fedayeen attacks in J & K is 62.5%.
As in the previous cases, this rule has two preconditions.
As in the previous cases, this rule has two preconditions.
(C12) India has released LeT prisoners.
We do not endorse any of these specific policies, and grant that making these changes will not be easy or without other consequnces. Bombing LeT training camps could unleash a firestorm of criticism from Pakistani leaders. In this paper, we have only studied actions within J & K — it is possible that LeT could retaliate elsewhere (e.g., in India or within Pakistan itself). The problem of reining in LeT is intractable precisely because there are no easy options. A policy is any subset of the set { C1,C2, C8, C9, C12 } of actionable conditions. Letus see what the impact of some of these subsets will be.
• Suppose we consider a policy {C1,C2}, punishing orga- nizations (banks, businesses) and individuals transactingbusiness with LeT. Our 10 rules say that this will have Fig. 1. List of behavioral rules discussed in this paper—applicable to actions some impact on LeT attacks on Indian security forces in J & K because two of the rules (Rules 1,2) will no longerapply. Another 3 rules regarding such attacks still havevalid pre-conditions. A policy taking only these steps will (C10) LeT is trying to ensure compliance (in Pakistan) with have no impact on murders or fedayeen attacks in J & K.
• Suppose we consider a policy consisting of {C1,C8,C12 In contrast, when either of these two conditions is false, }. In this case, the same rules that triggered potential the probability of LeT carrying out fedayeen attacks in J & K armed clashes between LeT and Indian security forces drops down dramatically to just 0.027%.
no longer apply. In addition, changing condition C8 will The clear message from the last three rules is that India reduce murders in J & K (Rule 6). By changing C12 to must not release LeT prisoners as a gesture of goodwill.
ensure that Indian security forces do not easily release LeT prisoners, there is a likelihood that two rules (Rules9, 10) about fedayeen attacks will not apply, leading to a potential decrease in the number of fedayeen attackscarried out by LeT in J & K.
Figure 1 shows the 10 rules we have presented in the Condition C9, reducing Pakistani military support for LeT, preceding section. These rules are derived from our LeT open may provide a policy for reducing the violent activity of LeT source data set. The probability of the action is shown at the in J & K. Pakistan’s military can be induced to limit its support beginning of the rule. These rules can serve a policy-maker in for LeT and reduce infiltration into J & K. According to Indian two ways. First, policy-makers can consider the predictions government statistics, the number of terrorist incidents and when applying resources. Rule 4 predicts an increase in casualties in J & K has declined over the past decade. Stephen LeT violence when Pakistan is undergoing social strife and Tankel, of the Carnegie Endowment for International Peace suffering from natural disasters. When these events occur, cites several cases when Pakistan’s military clamped down on Indian policy-makers deploy reserve forces to J & K to counter LeT operations, such as early 2004 when Pakistan and India the predicted upsurge in LeT activity. Secondly, a policy- engaged in talks, and summer 2005 when the London bomb- maker examining these rules could identify policy options that ings highlighted Pakistan’s role in terrorist training. Pakistan’s could change the conditions contributing to attacks on Indian military has not dismantled the terrorist infrastructure, but has security forces, fedayeen attacks, or murders in J & K. Some limited its proxies’ activities when terrorism contradicted its of these conditions are potentially actionable (e.g., C1,C2, interests. Source: “Jammu and Kashmir Assessment C8, C9, C12), while others are much harder to change (e.g., 2011,” South Asia Terrorism Portal, URL: http://www.satp.
org/satporgtp/countries/india/states/jandk/index.html.
• C1 is actionable because US and EU regulators can Tankel notes that pursuing this policy may have unintended punish banks and individuals sending illicit money to consequences. LeT has built its own operational infrastructure entities in Pakistan that are linked to LeT.
and, as the J & K front was limited, LeT may have turned its • C2 is actionable because the ability of LeT to con- attention to carrying out attacks in the rest of India [8].
duct legitimate revenue-generating businesses can also beseverely reduced by taking appropriate steps.
• C8 is actionable through military action to reduce the The behavior of terror organizations, such as LeT, is ability of LeT training camps in Pakistan to operate.
difficult to forecast and understand, due to the confluence of • C9 is actionable because the US may be able to influence many factors that must be considered. The complexity and the Pakistani military to reduce their support of LeT.
dynamism of terror group behavior has made development of • C12 is actionable as India can hold LeT prisoners until well-grounded statistical models difficult. Several works [9], their term is over, or pass legislation to extend terms.
[10] have developed hidden Markov models to describe how a conflict might evolve over time or to analyze the severity and frequency of terrorist attacks according to a power law [1] “Worldwide incidents tracking system,” National Counterterrorism distribution [11], [12]. However, these statistical methods Center, 2011. [Online]. Available: https://wits.nctc.gov make broad, long-range forecasts or post analyses, making [2] G. Simari, A. Sliva, D. Nau, and V. S. Subrahmanian, “A stochastic language for modelling opponent agents,” in AAMAS ’06: Proceedings them unsuitable for decision-support and policy making.
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to use both expert knowledge and computational analysis for [13] V. Subrahmanian, M. Albanese, V. Martinez, D. Reforgiato, G. Simari, A. Sliva, O. Udrea, and J. Wilkenfeld, “CARA: A Cultural Reasoning purposes of behavioral modeling and decision-making. LeT Architecture,” IEEE Intelligent Systems, vol. 22, no. 2, pp. 12–16, 2007.
in particular has become the subject of a significant body of [14] V. S. Subrahmanian, “Cultural modeling in real-time,” Science, vol. 317, research, especially since the Mumbai attacks in 2008. [21], no. 5844, pp. 1509–1510, Sep. 14 2007.
[15] A. Sliva, V. Subrahmanian, V. Martinez, and G. Simari, “Cape: Au- [22], and [23] focus on the details of these attacks and their tomatically predicting changes in group behavior,” in Mathematical potential future implications. Other work [24] provides an Methods in Counterterrorism, N. Memon, J. D. Farley, D. L. Hicks, overview of the group’s evolution leading up to Mumbai and Springer Verlag, 2009, pp. 247–263.
[16] A. Mannes, M. Michael, A. Pate, A. Sliva, V. Subrahmanian, and the future of terrorism in India, focusing on the role of LeT [5], J. Wilkenfeld, “Stochastic opponent modeling agents: A case study [8]. Our approach is the first data-driven attempt to analyze with hezbollah,” in First International Workshop on Social Computing, LeT’s behavior using systemically collected, highly structured Behavioral Modeling, and Prediction, April 2008.
[17] A. Mannes, A. Sliva, V. Subrahmanian, and J. Wilkenfeld, “Stochastic data regarding their historical context and actions, providing a opponent modeling agents: A case study with hamas,” in Proceedings computational approach that can help decision-makers identify of the Second International Conference on Computational Cultural The analyses presented above suggest several policies.
[18] A. Sliva, V. S. Subrahmanian, V. Martinez, and G. I. Simari, “The SOMA terror organization portal (STOP): Social network and analytic tools 1) India should not release LeT prisoners for the real-time analysis of terror groups,” in Proc. 2008 First Intl.
2) LeT’s international fundraising should be cut off Workshop on Social Computing, Behavioral Modeling and Prediction.
Spring Verlag Lecture Notes in Computer Science, April 2008, pp. 9–18.
3) LeT’s business operations in Pakistan should be closed [19] J. Stern, “Terror in the name of god: Why religious militants kill,” Ecco, 4) LeT training camps need to be closed down 5) Pressure Pakistan’s military to cease its support for LeT [20] B. Ganor, “The counter-terrorism puzzle: A guide for decision makers,” There are no guarantees that these policies can be imple- [21] J. Wilson and K. Vishwas, Investigating the Mumbai Conspiracy.
mented or that if implemented they will reduce LeT violence.
However, this paper represents an evolution in the study of [22] S. Rotella, Pakistan and the Mumbai Attacks: The Untold Story. ProP- terrorist group behavior. This is the first paper that collects data [23] C. C. Fair, “Antecedents and implications of the november 2008 lashkar- and analyzes LeT’s behavior in a systematic and structured e-taiba (let) attack upon several targets in the indian mega-city of manner. This process will ultimately allow policy-makers to mumbai,” Testimony presented before the House Homeland SecurityCommittee, Subcommittee on Transportation Security and Infrastructure apply the same kinds ofdata analytic tools to counterterrorism Protection on March 11, 2009, March 2009.
and other critical national security functions that companies [24] S. Tankel, “Lashkar-e-taiba: From 9/11 to mumbai,” Developments in like Google and Amazon already use to advise customers on Radicalisation and Political Violence, International Centre for the Studyof Radicalisation and Political Violence, April/May 2009.

Source: http://shakarian.net/janaPapers/let_eisic_camera.pdf