TY - CONF
T1 - Strategic social network analysis
AU - Michalak, Tomasz P.
AU - Rahwan, Talal
AU - Wooldridge, Michael
N1 - Funding Information:
We thank all the reviewers for their helpful comments. Michael Wooldridge and Tomasz P. Michalak were supported by the European Research Council under Advanced Grant 291528 (“RACE”). Tomasz P. Michalak was also supported by the Polish National Science Centre grant 2014/13/B/ST6/01807.
Publisher Copyright:
© Copyright 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2017
Y1 - 2017
N2 - How can individuals and communities protect their privacy against social network analysis tools? How do criminals or terrorists organizations evade detection by such tools? Under which conditions can these tools be made strategy proof? These fundamental questions have attracted little attention in the literature to date, as most social network analysis tools are built around the assumption that individuals or groups in a network do not act strategically to evade such tools. With this in mind, we outline in this paper a new paradigm for social network analysis, whereby the strategic behaviour of network actors is explicitly modeled. Addressing this research challenge has various implications. For instance, it may allow two individuals to keep their relationship secret or private. It may also allow members of an activist group to conceal their membership, or even conceal the existence of their group from authoritarian regimes. Furthermore, it may assist security agencies and counter terrorism units in understanding the strategies that covert organizations use to escape detection, and give rise to new strategy-proof countermeasures.
AB - How can individuals and communities protect their privacy against social network analysis tools? How do criminals or terrorists organizations evade detection by such tools? Under which conditions can these tools be made strategy proof? These fundamental questions have attracted little attention in the literature to date, as most social network analysis tools are built around the assumption that individuals or groups in a network do not act strategically to evade such tools. With this in mind, we outline in this paper a new paradigm for social network analysis, whereby the strategic behaviour of network actors is explicitly modeled. Addressing this research challenge has various implications. For instance, it may allow two individuals to keep their relationship secret or private. It may also allow members of an activist group to conceal their membership, or even conceal the existence of their group from authoritarian regimes. Furthermore, it may assist security agencies and counter terrorism units in understanding the strategies that covert organizations use to escape detection, and give rise to new strategy-proof countermeasures.
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M3 - Paper
AN - SCOPUS:85030477232
SP - 4841
EP - 4845
T2 - 31st AAAI Conference on Artificial Intelligence, AAAI 2017
Y2 - 4 February 2017 through 10 February 2017
ER -