Institute of Computing Technology, Chinese Academy IR
Optimal defense against election control by deleting voter groups | |
Yin, Yue1; Vorobeychik, Yevgeniy2; An, Bo3; Hazon, Noam4 | |
2018-06-01 | |
发表期刊 | ARTIFICIAL INTELLIGENCE |
ISSN | 0004-3702 |
卷号 | 259页码:32-51 |
摘要 | 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 defense against election control, including destructive and constructive 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 consider plurality voting, and show that it is computationally hard to prevent both types of control, though destructive control itself can be performed in polynomial time. For defense against destructive control, we present a double-oracle framework for computing an optimal prevention strategy. We show that both defender and attacker best response subproblems are NP-complete, and develop exact mixed-integer linear programming approaches for solving these, as well as fast heuristic methods. We then extend this general approach to develop effective algorithmic solutions for defense against constructive control. Finally, we generalize the model and algorithmic approaches to consider uncertainty about voter preferences. Experiments conducted on both synthetic and real data demonstrate that the proposed computational framework can scale to realistic problem instances.(1) (C) 2018 Elsevier B.V. All rights reserved. |
关键词 | Election control Protecting elections Security games |
DOI | 10.1016/j.artint.2018.02.001 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Science Foundation[CNS-1238959] ; National Science Foundation[IIS-1526860] ; National Science Foundation[IIS-1649972] ; Office of Naval Research[N00014-15-1-2621] ; Army Research Office[W911NF-16-1-0069] ; AFRL[FA8750-14-2-0180] ; Israel Science Foundation[1488/14] ; [NRF2015NCR-NCR003-004] |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000432512700002 |
出版者 | ELSEVIER SCIENCE BV |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/5283 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Yin, Yue; Vorobeychik, Yevgeniy |
作者单位 | 1.Univ Chinese Acad Sci, CAS, ICT, Key Lab Intelligent Informat Proc, Beijing, Peoples R China 2.Vanderbilt Univ, Elect Engn & Comp Sci, 221 Kirkland Hall, Nashville, TN 37235 USA 3.Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore, Singapore 4.Ariel Univ, Dept Comp Sci, Ariel, Israel |
推荐引用方式 GB/T 7714 | Yin, Yue,Vorobeychik, Yevgeniy,An, Bo,et al. Optimal defense against election control by deleting voter groups[J]. ARTIFICIAL INTELLIGENCE,2018,259:32-51. |
APA | Yin, Yue,Vorobeychik, Yevgeniy,An, Bo,&Hazon, Noam.(2018).Optimal defense against election control by deleting voter groups.ARTIFICIAL INTELLIGENCE,259,32-51. |
MLA | Yin, Yue,et al."Optimal defense against election control by deleting voter groups".ARTIFICIAL INTELLIGENCE 259(2018):32-51. |
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