Towards analyzing adversarial behavior in clandestine networks

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

*Corresponding author for this work

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

Abstract

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
Pages75-76
Number of pages2
VolumeWS-11-06
StatePublished - Oct 31 2011
Event2011 AAAI Workshop - San Francisco, CA, United States
Duration: Aug 7 2011Aug 7 2011

Other

Other2011 AAAI Workshop
CountryUnited States
CitySan Francisco, CA
Period8/7/118/7/11

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Ahmad, M. A., Keegan, B., Sullivan, S., Williams, D., Srivastava, J., & Contractor, N. (2011). Towards analyzing adversarial behavior in clandestine networks. In Applied Adversarial Reasoning and Risk Modeling - Papers from the 2011 AAAI Workshop, Technical Report (Vol. WS-11-06, pp. 75-76)