Enhanced BAN-GZKP: Optimal Zero Knowledge Proof Based Scheme in Body Area Networks

Abstract

A network of embedded sensors on the human body called Wireless Body Area Network (WBAN) has recently emerged as a healthcare monitoring framework, to provide better medical services. The data collected by these sensors is transmitted via a wireless medium and contains sensitive information of the patients. Therefore, how to provide security schemes for WBAN with resource constraints devices remains a big challenge. Recently, BAN-GZKP, an authentication scheme based on Zero-Knowledge Proof (ZKP) was designed for WBAN as an optimal solution to several attacks suffered by another ZKP based protocol called BANZKP. However, BAN-GZKP is found to be vulnerable to Node Compromise Attack, Node Impersonation, and Denial-of-Service Attacks. To fix the vulnerabilities of BANGZKP, this paper proposes an enhanced BAN-GZKP which exploits a unique physical layer characteristic coming from the surrounding WBAN, i.e., the distinct received signal strength variation among on-body channels and between on-body and off-body channels, to ensure robust authentication. To prove the reliability of our proposal, we conducted real-world experiments on 3 subjects in indoor and outdoor areas. The results showed that our scheme improves the security of the previous scheme with even lesser cost.