Optimal Voting Strategy against Random and Targeted Attacks

Optimal Voting Strategy against Random and Targeted Attacks

Li Wang, Zheng Li, Shangping Ren, Kevin Kwiat
Copyright: © 2013 |Pages: 22
DOI: 10.4018/ijsse.2013100102
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Replication and value selection through voting are commonly used approaches to tolerating naturally caused failures. Without considering intentionally introduced failures, such as failures caused by attacks, having more replication or residency often makes the system more reliable. However, when both the reliability of individual replicas and the existence of attackers are taken into consideration, the number of replicas that participate in a voting process has significant impact on system reliability. In this paper, the authors study the problem of deciding the optimal number of participating voters that maximizes the reliability of voting results under two different types of attacks, i.e., random attack and targeted attack, and develop algorithms to find the optimal voting strategy. A set of experiments are performed to illustrate how the optimal voting strategy varies under different system settings and how the number of voting participants affects the system's reliability.
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The analysis of attacker-defender problems have been studied from different perspectives. For instance, in Vicki and Bier (2002), Bier, Nagaraj, and Abhichandani (2005), Bier et al. study optimal defenses against intentional threats for both series and parallel systems, and illustrate how the optimal allocation of defensive investments changes with the structure of the system and the adversary's goals and constraints. Yalaoui et al. consider redundant components in series systems and proposed a dynamic programming method to calculate the minimum cost required for a system to satisfy the minimum reliability requirement (Yalaoui, Chatelet, & Chu, 2005).

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