Information Entropy Models and Privacy Metrics Methods for Privacy Protection

Hui Xia ； Weiji Yang

《International Journal of Network Security》 24卷1期 (2022/01) Pp. 1-10

https://doi.org/10.6633/IJNS.202201_24(1).01

摘要

The quantification of privacy plays an important role in privacy protection. It can be used to solve privacy metrics as a quantitative measure of information. To realize the privacy metrics, some models of privacy information entropy are proposed according to Shannon's Information Theory. Those models include the basic information entropy model of privacy protection, the information entropy model of privacy protection with adversary, the information entropy model of privacy protection with subjective feelings and multi-source information entropy model of privacy protection. In those models, the information owner is assumed to be the sender, privacy attacker is assumed as to be the recipient, and the privacy disclosure course can be regarded as a communication channel. Based on those assumptions, the entropy, mutual information, conditional entropy, and conditional mutual information are introduced to describe measurement of privacy, privacy disclosure, and privacy and disclosure with background knowledge for the privacy protection system. Furthermore, the quantitative evaluation of privacy protection strength and adversary ability is provided to support quantitative risk assessment for privacy disclosure. Finally, the specific information entropy model, measurement and analysis of privacy protection algorithms, and adversary ability are supplied for location privacy protection application. The proposed models and the privacy metrics can be used to analyze and evaluate the privacy protection technology and privacy disclosure risk assessment.

關鍵字

Communication Model ； Information Entropy Model ； Privacy Measurement ； Privacy Protection