Context-Aware Privacy Preservation in Network Caching: An Information Theoretic Approach

Caching has been recognized as a viable solution to surmount the limited capability of backhaul links in handling abundant network traffic. Although optimal approaches for minimizing the average delivery load do exist, current caching strategies fail to avert intelligent adversaries from obtaining invaluable contextual information by inspecting the wireless communication links and thus, violating users' privacy. Grounded in information theory, in this letter, we propose a mathematical model for preserving privacy in a network caching system involving a server and a cache-aided end user. We then present an efficient content caching method that maximizes the degree of privacy preservation while maintaining the average delivery load at a given level. Given the Pareto optimal nature of the proposed epsilon-constraint optimization approach, we also obtain the maximum privacy degree achievable under any given average delivery load. Numerical results and comparisons validate the correctness of our context-oriented privacy model.

Automated summary

In this letter, a mathematical model is proposed to preserve privacy in a network caching system involving a server and a cache-aided end user. An efficient content caching method is presented to maximize privacy preservation while maintaining the average delivery load at a given level. The Pareto optimal nature of the proposed epsilon-constraint optimization approach allows for achieving the maximum privacy degree possible under any given average delivery load.