TY - JOUR
T1 - A Privacy-Aware Medical Record Query Scheme with Anonymous Authentication in Wireless Body Area Networks
AU - Xie, Yuqi
AU - Zhao, Tao
AU - Peng, Tu
AU - Xiong, Ling
AU - Liu, Zhicai
AU - Xiong, Neal
N1 - Publisher Copyright:
© 2026 IEEE.
PY - 2026
Y1 - 2026
N2 - With the integration of intelligent medical devices and wireless sensor networks, telemedicine queries have significantly enhanced the efficiency and accessibility of medical services. However, the security and privacy of medical query records remain a critical challenge. While existing privacy-preserving query frameworks in Wireless Body Area Networks (WBANs) primarily focus on protecting the privacy of medical records, they often lack robust mechanisms for authenticating query users. This deficiency may enable malicious entities to gain unauthorized access, thereby resulting in data leakage. To address this issue, we propose a privacy-preserving query scheme with unlinkability by integrating double-Schnorr-based anonymous authentication and 1-out-of-n oblivious transfer (OT). Specifically, anonymous authentication is achieved via a double-Schnorr-based credential construction with session-dependent pseudonym blinding, enabling the server to verify user legitimacy without revealing users' real identities. OT is implemented through a short-hash-based keyword partition mechanism and masked encryption, ensuring that the curious server cannot infer user queries while fulfilling them correctly. Additionally, query privileges are restricted to legitimate users by verifying anonymous credentials issued during the registration phase. The formal security analysis confirms that the proposed scheme achieves essential security attributes, including anonymous authentication, query privacy, and unlinkability. Experimental results demonstrate that the proposed scheme not only integrates anonymous authentication but also outperforms baseline schemes in both computational and communication efficiency. Therefore, the proposed scheme is more suitable for real-world deployment within IoT-based healthcare ecosystems.
AB - With the integration of intelligent medical devices and wireless sensor networks, telemedicine queries have significantly enhanced the efficiency and accessibility of medical services. However, the security and privacy of medical query records remain a critical challenge. While existing privacy-preserving query frameworks in Wireless Body Area Networks (WBANs) primarily focus on protecting the privacy of medical records, they often lack robust mechanisms for authenticating query users. This deficiency may enable malicious entities to gain unauthorized access, thereby resulting in data leakage. To address this issue, we propose a privacy-preserving query scheme with unlinkability by integrating double-Schnorr-based anonymous authentication and 1-out-of-n oblivious transfer (OT). Specifically, anonymous authentication is achieved via a double-Schnorr-based credential construction with session-dependent pseudonym blinding, enabling the server to verify user legitimacy without revealing users' real identities. OT is implemented through a short-hash-based keyword partition mechanism and masked encryption, ensuring that the curious server cannot infer user queries while fulfilling them correctly. Additionally, query privileges are restricted to legitimate users by verifying anonymous credentials issued during the registration phase. The formal security analysis confirms that the proposed scheme achieves essential security attributes, including anonymous authentication, query privacy, and unlinkability. Experimental results demonstrate that the proposed scheme not only integrates anonymous authentication but also outperforms baseline schemes in both computational and communication efficiency. Therefore, the proposed scheme is more suitable for real-world deployment within IoT-based healthcare ecosystems.
KW - Wireless body area networks
KW - anonymous authentication
KW - oblivious transfer
KW - privacy-preserving query
UR - https://www.scopus.com/pages/publications/105041058062
U2 - 10.1109/JIOT.2026.3699575
DO - 10.1109/JIOT.2026.3699575
M3 - Article
AN - SCOPUS:105041058062
SN - 2327-4662
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
ER -