基于密度峰值的网络用户信息聚类局部自适应加密研究

Research on Local Adaptive Encryption of Network User Information Clustering based on Density Peaks

传统的加密方法对用户行为和约束条件的划分结果不佳,导致加密后的信息存在局部可识别,因此提出基于密度峰值的网络用户信息聚类局部自适应加密方法。该方法基于密度峰值重新聚类分析网络用户信息;利用混沌系统获取网络用户不确定行为特征;通过多目标追踪不同数据优先级,实现对信息自适应的精准控制;根据约束条件和限制条件调整聚类局部信息,实现全方位的信息加密。根据实验测试结果可知:与传统方法相比,所提出加密方法加密后的网络用户信息被完全覆盖,可识别率为0。由此可见,该方法的加密效果更好。

The traditional encryption method has poor results in dividing user behaviors and constraints,which leads to local identifiability of the encrypted information.Therefore,a local adaptive encryption method based on density peaks for network user information clustering was proposed.This method re-clusteres and analyzes network user information based on density peaks,uses chaotic systems to obtain network user uncertain behavior characteristics,tracks multiple data priorities through multiple targets to achieve precise and adaptive control of information,adjusts and clusters the local information according to the constraints and restrictions to realize comprehensive information encryption.According to the experimental test results,compared with the traditional method,the network user information encrypted by the proposed encryption method is completely covered,and the recognition rate is 0.It can be seen that the encryption effect of this method is better.