Reshaping terrorist networks

Francesca Spezzano, V. S. Subrahmanian, Aaron Mannes

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


The STONE algorithms identify a set of operatives whose removal would maximally reduce lethality to destabilize terrorist organizations. STONE uses three novel algorithms, Terrorist Successor Problem (TSP), Multiple Terrorist Successor Problem (MTSP), and Terrorist Network Reshaping Problem (TNRP). Measuring lethality of terrorist networks, STONE algorithms help predict who will succeed a removed terrorist leader with over 80% accuracy. STONE develops a mathematical model of who replaces a removed individual in a terrorist network, taking into account both network structure and vertex properties, as well as the need for the terrorist network to achieve operational effectiveness. A terrorist organization network (ON) is an undirected graph with vertices and edges. Each vertex is labeled with some properties drawn from a set VP of properties. STONE allows an analyst to specify any set of properties a vertex should have in order to be an appropriate replacement node for a vertex that is being removed.

Original languageEnglish (US)
Pages (from-to)60-69
Number of pages10
JournalCommunications of the ACM
Issue number8
StatePublished - Aug 2014
Externally publishedYes

ASJC Scopus subject areas

  • Computer Science(all)


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