关键词: 无线传感器网络, 恶意节点检测, 模糊信任模型, 贝叶斯信念估计, 安全威胁防御

Abstract: The application of wireless sensor networks (WSN) in various fields such as environmental monitoring and healthcare is gradually becoming widespread. However, sensor nodes in WSN are vulnerable to security threats, especially dishonest recommendation attacks initiated by malicious nodes, which may compromise communication integrity. Therefore, detecting malicious nodes in WSN is particularly important. 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 techniquefor 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 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.

Key words: wireless sensor networks (WSN), malicious node detection, fuzzy trust model, Bayesian belief estimation, security threat defense