Distributed privacy protection strategy for MEC enhanced wireless body area networks

Abstract With the rapid development and widespread application of Wireless Body Area Networks (WBANs), the traditional centralized system architecture cannot handle the massive data generated by the edge devices. Meanwhile, in order to ensure the security of physiological privacy data and the identity privacy of patients, this paper presents a privacy protection strategy for Mobile Edge Computing(MEC) enhanced WBANs, which leverages the blockchain-based decentralized MEC paradigm to support efficient transmission of privacy information with low latency, high reliability within a high-demand data security scenario. On this basis, the Merkle tree optimization model is designed to authenticate nodes and to verify the source of physiological data. Furthermore, a hybrid signature algorithm is devised to guarantee the node anonymity with unforgeability, data integrity and reduced delay. The security performance analysis and simulation results show that our proposed strategy not only reduces the delay, but also secures the privacy and transmission of sensitive WBANs data.