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

Seyedeh Bahereh Hassanpour, Abolfazl Diyanat, Ahmad Khonsari, Seyed Pooya Shariatpanahi, Aresh Dadlani

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Article number9186673
Pages (from-to)54-58
Number of pages5
JournalIEEE Communications Letters
Issue number1
Publication statusPublished - Jan 2021


  • Content caching
  • context-oriented privacy
  • error probability bound
  • information theory
  • Pareto optimal

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

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