Research on Data Privacy Protection and Heterogeneous Data Fusion of Joint Learning in Intelligent Sensor Networks

The traditional information fusion technology between WSN nodes is faced with the weak privacy protection ability of users, and the required communication traffic is large. Under this background, this paper designs and implements a new information security mechanism. The realization process and method of this method are introduced. A fusion algorithm based on segmented encryption is adopted to protect the privacy of users. The method uses local data interaction mechanism to reduce redundant information interaction in the collusive process, and adopts random transmission mechanism to improve the accuracy of fusion results. TOSSIM technology is used to verify the proposed data transmission capability, privacy protection capability and data fusion accuracy. Scalable data fusion technology and fragment encryption technology are adopted to ensure the confidentiality of information. Experimental results show that the proposed method can improve the communication efficiency and fusion effect greatly. The research results of this project can effectively improve the security protection ability of WSN for typical information.