Target Identity Recognition Method based on Trusted Information Fusion

摘要

Safe and reliable target identity recognition is the important foundation of information security. In the complex environment of multi-source target information, in view of the potential impact of many uncertain factors on target identity recognition and the performance requirements of information security in the process of recognition, a trusted target identity recognition method is proposed in this paper. The BP neural network based on momentum factor is used to study and build an ensemble classification model, and based on this model, the trusted target identity recognition model is constructed. According to the relevant information characterized by the model, it can improve the recognition reliability of the target to a certain extent, thus providing more security and credibility for the recognition of the identified target. Finally, the effectiveness and feasibility of the proposed algorithm is verified by simulation experiments under an uncertain set environment.