中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 计算技术研究所
  3. 中国科学院计算技术研究所
  4. 中国科学院计算技术研究所期刊论文
  5. 英文
Optimal defense against election control by deleting voter groups

文献类型：期刊论文

作者Yin, Yue3; Vorobeychik, Yevgeniy2; An, Bo4; Hazon, Noam1
刊名ARTIFICIAL INTELLIGENCE
出版日期2018-06-01
卷号259页码:32-51
关键词Election control Protecting elections Security games
ISSN号0004-3702
DOI10.1016/j.artint.2018.02.001
英文摘要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.
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
语种英语
WOS记录号WOS:000432512700002
出版者ELSEVIER SCIENCE BV
源URL[http://119.78.100.204/handle/2XEOYT63/5282]  
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.Ariel Univ, Dept Comp Sci, Ariel, Israel
2.Vanderbilt Univ, Elect Engn & Comp Sci, 221 Kirkland Hall, Nashville, TN 37235 USA
3.Univ Chinese Acad Sci, CAS, ICT, Key Lab Intelligent Informat Proc, Beijing, Peoples R China
4.Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore, Singapore
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.

入库方式： OAI收割

来源：计算技术研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。