Privacy-oriented Coded Caching in Mobile Information-centric Networking

Wireless network communication has the characteristics of broadcasting and bandwidth limitation, which makes it difficult for devices in the wireless network to obtain high-quality privacy protection and service. The difficulty of achieving both privacy and service quality exacerbates the challenge of privacy-oriented content caching optimization. To solve this problem, coded caching technology offers a new way, but there is little research on the integration of this technology with privacy protection. We propose a privacy-protecting coded caching framework named PCC for mobile Information-Centric Networks (ICNs). Firstly, we discuss the privacy leakage problems existing in the uncoded caching techniques of ICNs and propose an effective adversary model and a privacy protection strength evaluation model for caching in ICNs based on the Shannon cipher system. Secondly, we design a content encoding mechanism based on machine learning to solve the privacy leakage issue in caching, relying on a framework that predicts changes in network fluid nodes. We further propose a joint optimization problem for content caching and privacy protection and propose a privacy-oriented coded caching algorithm called PCC. Compared with existing solutions, our solution not only provides an improvement in privacy protection, but also achieves performance improvements in latency, throughput, and bandwidth savings.