On the construction of covert networks

Marcin Waniek, Talal Rahwan, Tomasz P. Michalak, Michael Wooldridge

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

Abstract

Centrality measures are widely used to identify leaders of covert networks. We study how a group of such leaders can avoid being detected by such measures. More concretely, we study the hardness of choosing a set of edges that can be added to the network in order to decrease the leaders' ranking according to two fundamental centrality measures, namely degree, and closeness. We prove that this problem is NP-complete for each measure. We then study how the leaders can construct a network from scratch, designed specifically for them to hide in disguise. We identify a network structure that not only guarantees to hide the leaders to a certain extent, but also allows them to spread their influence across the network.

Original languageEnglish (US)
Title of host publication16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017
EditorsEdmund Durfee, Michael Winikoff, Kate Larson, Sanmay Das
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1341-1349
Number of pages9
Volume3
ISBN (Electronic)9781510855076
StatePublished - Jan 1 2017
Event16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017 - Sao Paulo, Brazil
Duration: May 8 2017May 12 2017

Other

Other16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017
CountryBrazil
CitySao Paulo
Period5/8/175/12/17

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Keywords

  • Centrality
  • Hiding in networks
  • Social network analysis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

Cite this

Waniek, M., Rahwan, T., Michalak, T. P., & Wooldridge, M. (2017). On the construction of covert networks. In E. Durfee, M. Winikoff, K. Larson, & S. Das (Eds.), 16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017 (Vol. 3, pp. 1341-1349). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).