Secure and Privacy-Preserving Edge Caching in Next-Generation Mobile Networks

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Next-generation mobile networks (NGMNs) provide ultra-reliable and affordable broadband access everywhere, not only to cellular hand-carried devices, but also to a massive number of devices in machine-to-machine communications, cyber-physical systems, and Internet of Things. By integrating disruptive technologies, NGMNs are expected to support supremely high data rates and extremely low latency to enable emerging applications, e.g., remote control of smart vehicles, and virtual/augmented reality, thereby making our life more convenient. Mobile edge computing is a promising technology for NGMNs to offer service environment and cloud-computing capabilities in an effective manner at the edge of mobile networks. By exploiting the storage and computing resources at the network edge, popular contents can be temporarily maintained on cache-enabled edge nodes (e.g., macro base stations, Wi-Fi access points, and roadside infrastructure) for handling frequent data access requests from mobile users. Since the cached contents are delivered directly from edge nodes instead of from the remote cloud, it significantly reduces service latency, decreases network load, and improves user experience. Despite the appealing benefits of edge caching, it is vulnerable to a variety of cyber attacks, e.g., cache poisoning attacks and cache pollution attacks, which results in huge concerns of privacy, security and trust. The proposed research will address these concerns, particularly by considering privacy, security and trust threats in all aspects of mobile edge caching, including content placement, content delivery and content usage, which have not yet been comprehensively discussed in reported studies. Our objective is to design an efficient, secure and privacy-preserving edge-caching framework for NGMNs. Specifically, we will (1) propose privacy-preserving federated learning models for content placement to maximize the cache-hit rate, while preserving the privacy of mobile users; (2) design effective content locators on edge nodes for content exploration, and propose efficient key management mechanisms to support secure delivery of popular contents to a group of mobile users; (3) propose efficient content verification schemes based on the Blockchain for securing content usage, and build a trustful edge-caching framework by designing Blockchain-based auction and privacy-preserving smart contracts. The proposed research will help Canada establish and reinforce its leadership in ICT (Information and Communication Technologies). As such, new business models and revenue streams can be fostered and devised to ensure continued steady growth of the ICT sector in Canada. Through the program, 2 PhD, 3 MSc and 2 Undergraduate students will be trained as future researchers/engineers with expertise in cyber security, mobile communications and machine learning; these are crucial for the development of NGMNs, and will help to ensure a prosperous future for the Canadian ICT industry.