Enhanced Audit Bit Based Distributed Bayesian Detection in the Presence of Strategic Attacks
Chen Quan, Baocheng Geng, Yunghsiang S. Han, Pramod K. Varshney

TL;DR
This paper introduces enhanced audit bit schemes for distributed Bayesian detection that improve robustness against strategic Byzantine attacks and reduce communication overhead in wireless sensor networks.
Contribution
It proposes the EAS and RAS schemes with derived optimal fusion rules, demonstrating improved robustness and performance over traditional methods.
Findings
EAS outperforms TAS in detection accuracy and robustness.
RAS further improves detection and robustness over EAS and TAS.
RAS reduces communication overhead, extending network lifetime.
Abstract
This paper employs an audit bit based mechanism to mitigate the effect of Byzantine attacks. In this framework, the optimal attacking strategy for intelligent attackers is investigated for the traditional audit bit based scheme (TAS) to evaluate the robustness of the system. We show that it is possible for an intelligent attacker to degrade the performance of TAS to the system without audit bits. To enhance the robustness of the system in the presence of intelligent attackers, we propose an enhanced audit bit based scheme (EAS). The optimal fusion rule for the proposed scheme is derived and the detection performance of the system is evaluated via the probability of error for the system. Simulation results show that the proposed EAS improves the robustness and the detection performance of the system. Moreover, based on EAS, another new scheme called the reduced audit bit based scheme…
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Taxonomy
TopicsDistributed Sensor Networks and Detection Algorithms · Target Tracking and Data Fusion in Sensor Networks · Security in Wireless Sensor Networks
