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

下一代移动网络(NGMN)可在任何地方提供超可靠且经济实惠的宽带接入，不仅可接入蜂窝手持设备，还可接入机器对机器通信、网络物理系统和物联网中的大量设备。通过集成颠覆性技术，NGMN有望支持极高的数据速率和极低的延迟，以支持新兴应用，如智能汽车的远程控制，以及虚拟/增强现实，从而使我们的生活更加便利。移动边缘计算是下一代网状网在移动网络边缘有效提供服务环境和云计算能力的一种很有前途的技术。通过利用网络边缘的存储和计算资源，流行内容可以临时维护在启用缓存的边缘节点(例如，宏基站、Wi-Fi接入点和路边基础设施)上，以处理来自移动用户的频繁数据访问请求。由于缓存的内容直接从边缘节点分发，而不是从远程云分发，因此显著减少了服务延迟，降低了网络负载，改善了用户体验。尽管边缘缓存具有诱人的优势，但它容易受到各种网络攻击，例如缓存中毒攻击和缓存污染攻击，这导致了对隐私、安全和信任的极大担忧。 拟议的研究将解决这些问题，特别是通过考虑移动边缘缓存所有方面的隐私、安全和信任威胁，包括内容放置、内容交付和内容使用，这些问题在已报道的研究中尚未得到全面讨论。我们的目标是为下一代网状网设计一个高效、安全和隐私保护的边缘缓存框架。具体来说，我们将 (1)提出了基于隐私保护的联合学习模型，在保护移动用户隐私的同时最大化缓存命中率； (2)在边缘节点上设计有效的内容定位器用于内容探索，并提出高效的密钥管理机制来支持热门内容安全地传递给一群移动用户； (3)提出了基于区块链的高效内容验证方案，并通过设计基于区块链的拍卖和隐私保护智能合约，构建了一个可信的边缘缓存框架。 拟议的研究将帮助加拿大建立和加强其在信息和通信技术(ICT)方面的领导地位。因此，可以培育和设计新的商业模式和收入来源，以确保加拿大信息和通信技术部门的持续稳定增长。 通过该计划，2名博士、3名硕士和2名本科生将被培训为未来的研究人员/工程师，拥有网络安全、移动通信和机器学习方面的专业知识；这些对NGMN的发展至关重要，并将有助于确保加拿大ICT行业的繁荣未来。

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.