Optimally Protecting Elections

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 formulations 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.

[1]  David C. Parkes,et al.  A Complexity-of-Strategic-Behavior Comparison between Schulze's Rule and Ranked Pairs , 2012, AAAI.

[2]  Hong Liu,et al.  Parameterized complexity of control problems in Maximin election , 2010, Inf. Process. Lett..

[3]  Bo An,et al.  Security Games with Protection Externalities , 2015, AAAI.

[4]  Piotr Faliszewski,et al.  Weighted electoral control , 2013, AAMAS.

[5]  Avrim Blum,et al.  Planning in the Presence of Cost Functions Controlled by an Adversary , 2003, ICML.

[6]  Eric Wustrow,et al.  Attacking the Washington, D.C. Internet Voting System , 2012, Financial Cryptography.

[7]  Howard Straubing,et al.  Theory of Computing Systems , 2008 .

[8]  Kevin Leyton-Brown,et al.  SATzilla: Portfolio-based Algorithm Selection for SAT , 2008, J. Artif. Intell. Res..

[9]  Edith Hemaspaandra,et al.  More Natural Models of Electoral Control by Partition , 2014, ADT.

[10]  Piotr Faliszewski,et al.  Multimode Control Attacks on Elections , 2009, IJCAI.

[11]  Vincent Conitzer,et al.  Computing the optimal strategy to commit to , 2006, EC '06.

[12]  Garth P. McCormick,et al.  Computability of global solutions to factorable nonconvex programs: Part I — Convex underestimating problems , 1976, Math. Program..

[13]  G. Bonanno On the Logic of Common Belief , 1996, Math. Log. Q..

[14]  Piotr Faliszewski,et al.  Combinatorial voter control in elections , 2014, Theor. Comput. Sci..

[15]  Piotr Faliszewski,et al.  Elections with Few Voters: Candidate Control Can Be Easy , 2014, AAAI.

[16]  R. M. Dijkstra Information Processing Letters , 2003 .

[17]  Milind Tambe,et al.  Security and Game Theory - Algorithms, Deployed Systems, Lessons Learned , 2011 .

[18]  Sarit Kraus,et al.  Playing games for security: an efficient exact algorithm for solving Bayesian Stackelberg games , 2008, AAMAS.

[19]  Curtis Menton,et al.  Normalized Range Voting Broadly Resists Control , 2010, Theory of Computing Systems.

[20]  Vincent Conitzer,et al.  Security Games with Multiple Attacker Resources , 2011, IJCAI.

[21]  Zhen Wang,et al.  Computing Optimal Monitoring Strategy for Detecting Terrorist Plots , 2016, AAAI.

[22]  Jörg Rothe,et al.  Hybrid Elections Broaden Complexity‐Theoretic Resistance to Control , 2006, IJCAI.

[23]  Jörg Rothe,et al.  Sincere‐Strategy Preference‐Based Approval Voting Fully Resists Constructive Control and Broadly Resists Destructive Control , 2008, Math. Log. Q..

[24]  Jean-François Laslier,et al.  A live experiment on approval voting , 2008 .

[25]  张谷 实验经济学(Experimental Economics)研究思路及成果应用简述 , 1994 .

[26]  Yevgeniy Vorobeychik,et al.  Securing interdependent assets , 2012, Autonomous Agents and Multi-Agent Systems.

[27]  Alexis Tsoukiàs,et al.  Algorithmic Decision Theory: First International Conference, ADT 2009, Venice, Italy, October 20-23, 2009. Proceedings , 2009 .

[28]  Hong Liu,et al.  Parameterized computational complexity of control problems in voting systems , 2009, Theor. Comput. Sci..

[29]  Vincent Conitzer,et al.  Security scheduling for real-world networks , 2013, AAMAS.

[30]  Nadja Betzler,et al.  Parameterized complexity of candidate control in elections and related digraph problems , 2008, Theor. Comput. Sci..

[31]  Michael A. Trick,et al.  How hard is it to control an election? Math , 1992 .

[32]  Vincent Conitzer,et al.  Stackelberg vs. Nash in Security Games: An Extended Investigation of Interchangeability, Equivalence, and Uniqueness , 2011, J. Artif. Intell. Res..

[33]  J. van Leeuwen,et al.  Theoretical Computer Science , 2003, Lecture Notes in Computer Science.

[34]  Jörg Rothe,et al.  Anyone but him: The complexity of precluding an alternative , 2005, Artif. Intell..

[35]  Marco Aiello,et al.  AAAI Conference on Artificial Intelligence , 2011, AAAI Conference on Artificial Intelligence.

[36]  Dan S. Wallach,et al.  Hack-a-vote: Security issues with electronic voting systems , 2004, IEEE Security & Privacy Magazine.

[37]  Bo An,et al.  Security games with surveillance cost and optimal timing of attack execution , 2013, AAMAS.