Optimal Voting Strategy against Random and Targeted Attacks

Abstract

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.

Security Information and Event Management (SIEM): Analysis, Trends, and Usage in Critical Infrastructures

“…This requires the use of diversity, including but not limited to the use of multiple intrusion detection systems (IDSs) and disparate open-source intelligence data (e.g., infrastructure-related information about security from open-source intelligence data available on diverse sources from the internet). There has been only sparse research on how to choose among alternative layered defenses; occasionally, unsuitable models appear relying on the naive assumption of independent failures between the diverse components [ 80 ]. Security engineers have little or no theory to guide their decisions about diversity, although unaided intuition can be very misleading (e.g., Littlewood and Wright [ 81 ]).…”