Comments on “A Large-Scale Concurrent Data Anonymous Batch Verification Scheme for Mobile Healthcare Crowd Sensing”

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Original languageEnglish
Pages (from-to)1287-1290
Journal / PublicationIEEE Internet of Things Journal
Volume6
Issue number1
Online published2 Aug 2018
Publication statusPublished - Feb 2019

Abstract

As an important application of the Internet of Things technologies, mobile healthcare crowd sensing (MHCS) still has challenging issues, such as privacy protection and efficiency. Quite recently in the IEEE Internet of Things Journal (DOI: 10.1109/JIOT.2018.2828463), Liu et al. proposed a large-scale concurrent data anonymous batch verification scheme for MHCS, claiming to provide batch authentication, nonrepudiation, and anonymity. However, after a close look at the scheme, we point out that the scheme suffers two types of signature forgery attacks and hence fails to achieve the claimed security properties. In addition, a reasonable and rigorous probability analysis indicates that the security reduction from the security of the scheme to the hardness of the computational Diffie-Hellman problem is invalid. We hope that similar design flaws can be avoided in future design of anonymous batch verification schemes for MHCS.

Research Area(s)

  • Anonymity, Batch authentication., Cryptanalysis, Mobile healthcare crowd sensing

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