Optimally Protecting Elections
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 538-544.
Abstract
Election control encompasses attempts from an external agent to alter the structure of an election in order to change its outcome. This problem is both a fundamental theoretical problem in social choice, and a major practical concern for democratic institutions.Consequently, this issue has received considerable attention, particularly as it pertains to different voting rules. In contrast, the problem of how election control can be prevented or deterred has been largely ignored. We introduce the problem of optimal protection against election control, where manipulation is allowed at the granularity of groups of voters (e.g., voting locations), through a denial-of-service attack, and the defender allocates limited protection resources to prevent control. We show that for plurality voting, election control through group deletion to prevent a candidate from winning is in P, while it is NP-Hard to prevent such control. We then present a double-oracle framework for computing an optimal prevention strategy, developing exact mixed-integer linear programming for mulations for both the defender and attacker oracles (both of these subproblems we show to be NP-Hard), as well as heuristic oracles. Experiments conducted on both synthetic and real data demonstrate that the proposed computational framework can scale to realistic problem instances.
@inproceedings{ijcai2016p83,
title = {Optimally Protecting Elections},
author = {Yin, Yue and Vorobeychik, Yevgeniy and An, Bo and Hazon, Noam},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {538--544},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/83},
}
TY - CPAPER TI - Optimally Protecting Elections AU - Yin, Yue AU - Vorobeychik, Yevgeniy AU - An, Bo AU - Hazon, Noam T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 538 EP - 544 UR - https://ijcai.org/proceedings/2016/83 ER -Copied
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