Enhanced Audit Bit Based Distributed Bayesian Detection in the Presence of Strategic Attacks

Chen Quan, Baocheng Geng, Yunghsiang S. Han, Pramod K. Varshney

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

This paper employs an audit bit based mechanism to mitigate the effect of Byzantine attacks on distributed Bayesian detection systems. In this framework, the optimal attacking strategy for strategic 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 a strategic attacker to degrade the performance of TAS to the system without audit bits. To enhance the robustness of the system in the presence of strategic 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 (RAS) is proposed which further improves system performance. We derive the new optimal fusion rule and the simulation results show that RAS outperforms EAS and TAS in terms of both robustness and detection performance of the system. Then, we extend the proposed RAS for a wide-area cluster based distributed wireless sensor networks (CWSNs). Simulation results show that the proposed RAS significantly reduces the communication overhead between the sensors and the FC, which prolongs the lifetime of the network.

Original languageEnglish (US)
Pages (from-to)49-62
Number of pages14
JournalIEEE Transactions on Signal and Information Processing over Networks
Volume8
DOIs
StatePublished - 2022
Externally publishedYes

Keywords

  • Information processing
  • Probabilistic logic
  • Robustness
  • Security
  • Sensor systems
  • Sensors
  • Wireless sensor networks

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Computer Networks and Communications

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