Secure and Efficient Fog-Assisted Quantum-Inspired Wearable Healthcare Consumer Electronics IoT System
Zhendong Song, Tao Gong, Menglin Xie, Jinda Luo, Thippa Reddy Gadekallu, Mohammed Amoon, Chien‐Ming Chen, Saru Kumari, Ning Liu · IEEE Transactions on Consumer Electronics · 2024
The integration of wearable healthcare devices and fog computing has emerged as a promising paradigm for providing personalized and efficient healthcare solutions. However, the security and privacy concerns associated with the sensitive health data transmitted in such systems pose significant challenges. This paper proposes a secure and efficient fog-assisted wearable healthcare Internet of Things (IoT) system, which leverages physical layer security techniques and quantum-inspired resource allocation to enhance the confidentiality and performance of the system. First, we present a system model for a secure fog-assisted wearable healthcare IoT system, incorporating wearable healthcare devices, fog computing servers, and potential eavesdroppers. Next, we formulate an optimization problem with the goal of maximizing the secrecy rate of the system by allocating both spectral and computing resources jointly. Ultimately, we develop a bean optimization method influenced by quantum principles to address the issue of allocating resources collaboratively. The experimental findings show the efficacy of the suggested system and resource allocation strategy regarding secrecy rate performance under various scenarios.