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Efficient Group Blind Signature for Medical Data Anonymous Authentication in Blockchain-Enabled IoMT 被引量:1

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摘要 Blockchain technology promotes the development of the Internet of medical things(IoMT)from the centralized form to distributed trust mode as blockchain-based Internet of medical things(BIoMT).Although blockchain improves the cross-institution data sharing ability,there still exist the problems of authentication difficulty and privacy leakage.This paper first describes the architecture of the BIoMT system and designs an anonymous authentication model for medical data sharing.This BIoMT system is divided into four layers:perceptual,network,platform,and application.The model integrates an anonymous authentication scheme to guarantee secure data sharing in the network ledger.Utilizing the untampered blockchain ledger can protect the privacy of medical data and system users.Then,an anonymous authentication scheme called the group blind signature(GBS)scheme is designed.This scheme can provide anonymity for the signer as that one member can represent the group to sign without exposing his identity.The blind property also can protect the message from being signed as it is anonymous to the signer.More-over,this GBS scheme is created with the lattice assumption,which makes it more secure against quantum attacks.In addition,the security proof shows that this GBS scheme can achieve the security properties of dynamical-almost-full anonymity,blindness,traceability,and non-frameability.The comparison analysis and performance evaluation of key size show that this GBS scheme is more efficient than similar schemes in other literature.
出处 《Computers, Materials & Continua》 SCIE EI 2023年第7期591-606,共16页 计算机、材料和连续体(英文)
基金 supported by the National Natural Science Foundation of China under Grant 61962009 the Doctor Scientific Research Fund of Zhengzhou University of Light Industry under Grant 2021BSJJ033 the Key Scientific Research Project of Colleges and Universities in Henan Province(CN)underGrant No.22A413010 the Foundation and Cutting-Edge Technologies Research Program of Henan Province(CN)under Grant No.222102210161 the Natural Science Foundation of Henan Province(CN)under Grant No.222300420582.
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