群智感知中基于三支决策的恶意用户检测方法OA

Malicious users pose a significant security threat to mobile crowdsensing networks,se-verely impacting their service performance and data quality.However,existing binary(black-and-white)malicious user detection methods lack mechanisms for handling suspicious users,leaving persis-tent security vulnerabilities.To address this issue,this paper proposes a malicious user detection meth-od based on three-way decision.Firstly,an evaluation probability function is constructed using user be-havior,data quality,and user recommendations as evaluation metrics.Then,the three-way decision method is employed to classify users into three categories:trust-worthy users,suspicious users,and malicious users.Finally,the grey correlation analysis method is utilized to dynamically identify mali-cious users among the suspicious ones.Simulation experiments demonstrate that the proposed detection method performs well in terms of accuracy,false positive rate,and false negative rate,effectively en-hancing the security performance of mobile crowdsensing networks.