Abstract: When the current privacy protection algorithm for network users is implemented, the noise points in the data are not removed, which leads to long time-consuming encryption, low security index, and poor integrity, which seriously affects the application experience of network users. Therefore, a network based on probability statistics is proposed using privacy protection algorithm. First, the wavelet transform threshold method is used to reduce the noise of the data to eliminate the uncertain factors generated during the data collection, so that the algorithm consumes less time in the encryption process. In order to improve the security index of the algorithm, the analytic hierarchy process is used in probability statistics. On the basis of knowledge, a privacy protection hierarchical analysis model is established, and the model is used to encrypt the obtained privacy protection target value through the Logistic chaotic mapping system to realize the privacy protection of network users. The experimental comparison results show that the proposed algorithm has short time-consuming encryption, high security index and better integrity, and can be widely used.

Key words: Wavelet transform threshold method, noise reduction processing, knowledge of probability statistics, privacy protection analytic hierarchy model, Logistic chaotic mapping system