Towards analyzing adversarial behavior in clandestine networks

Muhammad Aurangzeb Ahmad, Brian Keegan, Sophia Sullivan, Dmitri Williams, Jaideep Srivastava, Noshir Contractor

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Adversarial behavioral has been observed in many different contexts. In this paper we address the problem of adversarial behavior in the context of clandestine networks. We use data from a massively multiplayer online role playing game to illustrate the behavioral and structural signatures of deviant players change over time as a response to "policing" activities of the game administrators. Preliminary results show that the behavior of the devant players and their affiliates show co-evolutionary behavior and the timespan within the game can be divided into different epochs based on their behaviors. Feature sets derived from these results can be used for better predictive machine learning models for detecting deviants in clandestine networks.

Original languageEnglish (US)
Title of host publicationApplied Adversarial Reasoning and Risk Modeling - Papers from the 2011 AAAI Workshop, Technical Report
Number of pages2
StatePublished - 2011
Event2011 AAAI Workshop - San Francisco, CA, United States
Duration: Aug 7 2011Aug 7 2011

Publication series

NameAAAI Workshop - Technical Report


Conference2011 AAAI Workshop
Country/TerritoryUnited States
CitySan Francisco, CA


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