On fighting fire with fire: Strategic destabilization of terrorist networks

Vahid Behzadan; Amin Nourmohammadi; Mehmet Gunes; Murat Yuksel

doi:10.1145/3110025.3119404

On fighting fire with fire: Strategic destabilization of terrorist networks

Vahid Behzadan
, Amin Nourmohammadi
, Mehmet Gunes
, Murat Yuksel

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

Terrorist organizations have social networks that enable them to recruit and operate around the world. This paper presents a novel computational framework for derivation of optimal destabilization strategies against dynamic social networks of terrorists. We develop a game-theoretic model to capture the distributed and complex dynamics of terrorist organizations, and introduce a technique for estimation of such dynamics from incomplete snapshots of target networks. Furthermore, we propose a mechanism for devising the optimal sequence of actions that drive the internal dynamics of targeted organizations towards an arbitrary state of instability. The performance of this framework is evaluated on a model of the Al-Qaeda network in 2001, verifying the efficacy of our proposals for counter-terrorism applications.

Original language	English
Title of host publication	Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017
Editors	Jana Diesner, Elena Ferrari, Guandong Xu
Pages	1120-1127
Number of pages	8
ISBN (Electronic)	9781450349932
DOIs	https://doi.org/10.1145/3110025.3119404
State	Published - 31 Jul 2017
Event	9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017 - Sydney, Australia Duration: 31 Jul 2017 → 3 Aug 2017

Publication series

Name	Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017

Conference

Conference	9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017
Country/Territory	Australia
City	Sydney
Period	31/07/17 → 3/08/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

Keywords

Counter terrorism
Dynamic network analysis
Guided self-organization
Network formation game
Reinforcement learning

Access to Document

10.1145/3110025.3119404

Cite this

Behzadan, V., Nourmohammadi, A., Gunes, M., & Yuksel, M. (2017). On fighting fire with fire: Strategic destabilization of terrorist networks. In J. Diesner, E. Ferrari, & G. Xu (Eds.), Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017 (pp. 1120-1127). (Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017). https://doi.org/10.1145/3110025.3119404

Behzadan, Vahid ; Nourmohammadi, Amin ; Gunes, Mehmet et al. / On fighting fire with fire : Strategic destabilization of terrorist networks. Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017. editor / Jana Diesner ; Elena Ferrari ; Guandong Xu. 2017. pp. 1120-1127 (Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017).

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title = "On fighting fire with fire: Strategic destabilization of terrorist networks",

abstract = "Terrorist organizations have social networks that enable them to recruit and operate around the world. This paper presents a novel computational framework for derivation of optimal destabilization strategies against dynamic social networks of terrorists. We develop a game-theoretic model to capture the distributed and complex dynamics of terrorist organizations, and introduce a technique for estimation of such dynamics from incomplete snapshots of target networks. Furthermore, we propose a mechanism for devising the optimal sequence of actions that drive the internal dynamics of targeted organizations towards an arbitrary state of instability. The performance of this framework is evaluated on a model of the Al-Qaeda network in 2001, verifying the efficacy of our proposals for counter-terrorism applications.",

keywords = "Counter terrorism, Dynamic network analysis, Guided self-organization, Network formation game, Reinforcement learning",

author = "Vahid Behzadan and Amin Nourmohammadi and Mehmet Gunes and Murat Yuksel",

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Behzadan, V, Nourmohammadi, A, Gunes, M & Yuksel, M 2017, On fighting fire with fire: Strategic destabilization of terrorist networks. in J Diesner, E Ferrari & G Xu (eds), Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017. Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017, pp. 1120-1127, 9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017, Sydney, Australia, 31/07/17. https://doi.org/10.1145/3110025.3119404

On fighting fire with fire: Strategic destabilization of terrorist networks. / Behzadan, Vahid; Nourmohammadi, Amin; Gunes, Mehmet et al.
Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017. ed. / Jana Diesner; Elena Ferrari; Guandong Xu. 2017. p. 1120-1127 (Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Yuksel, Murat

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N2 - Terrorist organizations have social networks that enable them to recruit and operate around the world. This paper presents a novel computational framework for derivation of optimal destabilization strategies against dynamic social networks of terrorists. We develop a game-theoretic model to capture the distributed and complex dynamics of terrorist organizations, and introduce a technique for estimation of such dynamics from incomplete snapshots of target networks. Furthermore, we propose a mechanism for devising the optimal sequence of actions that drive the internal dynamics of targeted organizations towards an arbitrary state of instability. The performance of this framework is evaluated on a model of the Al-Qaeda network in 2001, verifying the efficacy of our proposals for counter-terrorism applications.

AB - Terrorist organizations have social networks that enable them to recruit and operate around the world. This paper presents a novel computational framework for derivation of optimal destabilization strategies against dynamic social networks of terrorists. We develop a game-theoretic model to capture the distributed and complex dynamics of terrorist organizations, and introduce a technique for estimation of such dynamics from incomplete snapshots of target networks. Furthermore, we propose a mechanism for devising the optimal sequence of actions that drive the internal dynamics of targeted organizations towards an arbitrary state of instability. The performance of this framework is evaluated on a model of the Al-Qaeda network in 2001, verifying the efficacy of our proposals for counter-terrorism applications.

KW - Counter terrorism

KW - Dynamic network analysis

KW - Guided self-organization

KW - Network formation game

KW - Reinforcement learning

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Behzadan V, Nourmohammadi A, Gunes M, Yuksel M. On fighting fire with fire: Strategic destabilization of terrorist networks. In Diesner J, Ferrari E, Xu G, editors, Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017. 2017. p. 1120-1127. (Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017). doi: 10.1145/3110025.3119404

On fighting fire with fire: Strategic destabilization of terrorist networks

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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