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Incentivizing Secure Edge Caching for Scalable Coded Videos in Heterogeneous Networks

  • Shanghai University
  • Queen's University Kingston

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Edge caching has been envisioned as a promising technology in heterogeneous networks (HetNets) to proximally cache (video) contents. Nevertheless, as massive resources (e.g., energy, storage, computing, and bandwidth) are consumed to cache contents, edge caching devices (ECDs) are unwilling to provide caching services. In addition, as the ECDs are usually deployed by untrusted third parties, the cached contents may be illegally accessed, which results in the mobile users' privacy leakage. To efficiently address these problems, in this paper, we propose a novel secure edge caching scheme for video contents in HetNets. Specifically, to motivate the participation of ECDs, the Nash bargaining game is exploited to model the negotiations between the content provider and ECDs, where the optimal requested caching space of the content provider and the optimal caching price of each ECD are jointly analyzed. Apart from this, to protect the content secrecy, scalable video coding is employed to facilitate secure edge caching, where the ECDs are only utilized to cache the enhancement layers that cannot be independently decoded to reconstruct the original contents. Then, we formulate a non-convex 0-1 integer programming problem to optimize the enhancement layer caching on ECDs, and the modified alternating direction method of multipliers (ADMM) is used to solve the problem optimally. Finally, simulation results show that the proposed scheme provides secure and efficient content caching for mobile users.

Original languageEnglish
Pages (from-to)2480-2492
Number of pages13
JournalIEEE Transactions on Information Forensics and Security
Volume18
DOIs
StatePublished - 2023

Keywords

  • ADMM
  • Heterogenous networks (HetNets)
  • Nash bargaining game
  • scalable video coding
  • secure edge caching

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