Title: A hybrid malicious node detection approach based on fuzzy trust model and Bayesian belief in wireless sensor networks

Authors: Wuchao Shi

Addresses: Centre of Modern Educational Technology, Xi'an Aeronautical Polytechnic Institute, Xi'an, Shaanxi, China

Abstract: With the wide range of Wireless Sensor Network (WSN) applications including environmental monitoring and healthcare, the sensor nodes in WSN are susceptible to security threats including dishonest recommendation attacks from malicious nodes, which could disrupt communication's integrity. Thus, malicious node detection in WSN is essential. In recent years, several malicious node detection approaches based on trust management were proposed to protect the WSN against dishonest recommendation attacks. However, the existing approaches ignore data consistency and re-evaluation of participating nodes in trust evaluation, which seriously undermine their effectiveness. To address these limitations, we propose a hybrid malicious node detection technique for WSN based on the Fuzzy Trust Model (FTM) algorithm and the Bayesian Belief Estimation (BBE) approach. The key idea in the proposed approach is to determine direct trust values through the FTM algorithm using the correlation of data collected over time, and to ascertain the trustworthiness of indirect trust values from recommendation nodes via the BBE approach. The results of simulations conducted to evaluate the effectiveness of our approach show that our model can effectively detect malicious nodes in WSN better than the previous approaches.

Keywords: WSN; wireless sensor network; dishonest recommendation attacks; fuzzy trust model; Bayesian belief.

DOI: 10.1504/IJWMC.2024.139665

International Journal of Wireless and Mobile Computing, 2024 Vol.27 No.1, pp.56 - 63

Received: 02 Sep 2022
Received in revised form: 16 May 2023
Accepted: 09 Jun 2023
Published online: 05 Jul 2024 *

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