Construction of Communication Information Encryption Transmission System Based on Bayesian Algorithm
Hao Chen, Yuan Ji, Jiawei Wang, Jie Chen · 2023
Communication not only brings convenience to people, but also produces information. Malicious intrusion programs continue to threaten the network security in the network, resulting in a great threat to the privacy of users and becoming a potential safety hazard. In order to protect the security of network communication information, it is necessary to encrypt the key of communication message information. Naive Bayesian classification is an effective machine learning algorithm, which has important applications in text detection and medical diagnosis. In order to improve the security and real-time transmission of network communication information, this paper proposes a real-time encrypted transmission system of network communication information based on Bayesian algorithm, which can efficiently realize safe and naive Bayesian training and classification on encrypted data. The simulation results show that with the increase of the quantity of experiments, the accuracy of this algorithm is stable at about 95%, and the real-time wavelength tends to be stable, which is 18.85% higher than the traditional algorithm on average. The proposed scheme not only protects the privacy of outsourced data sets, naive Bayes model, samples to be classified and classification results, but also effectively reduces the computation and communication overhead. This method improves the security of the network and provides an effective guarantee for the security and real-time performance of the wireless communication network.