Secure and Trust-Oriented Edge Storage for Internet of Things

Abstract

The edge storage is a promising paradigm to support the Internet of Things (IoT) data storage, and is more efficient than the cloud storage in terms of the bandwidth overhead, the response latency, and so on. However, existing edge storage models cannot offer the security-aware data robustness and the adaptable data sharing among many uncertain users, due to the limitations of the utilized fault-tolerant storage technologies and the access control methods. In this article, we propose a secure and trust-oriented edge storage model, which would efficiently tackle the aforementioned two challenging issues in the IoT environment. More precisely, we first propose a robust and secure edge storage (RoSES) model using the totally local reconstruction code (TLRC) method presented in this article. It can achieve data robustness, high security, and lightweight computation at end devices. We further propose a trust-oriented data access (TODA) strategy for our RoSES model, which supports a wide and adaptable range of legitimate data accesses from uncertain requesters for IoT data sharing. We conduct extensive comparison and simulations to evaluate the performance of our new edge storage models. The results show that our model can efficiently realize the data storage, data recovery, and data sharing at the network edge, saving about 35% of storage cost and 76% degraded read latency. Besides, the data leakage probability is significantly reduced during the data storage and sharing processes.