Publication Type
Journal Article
Version
acceptedVersion
Publication Date
2-2019
Abstract
As an important application of the Internet of Things (IoT) technologies, mobile healthcare crowd sensing (MHCS) still has challenging issues, such as privacy protection and efficiency. Quite recently in 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 mobile healthcare crowd sensing, claiming to provide batch authentication, non-repudiation, 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 (CDH) problem is invalid. We hope that similar design flaws can be avoided in future design of anonymous batch verification schemes for mobile healthcare crowd sensing.
Keywords
Batch authentication, Cryptanalysis, Anonymity, Mobile healthcare crowd sensing
Discipline
Information Security | Medicine and Health Sciences
Publication
IEEE Internet of Things
Volume
6
Issue
1
First Page
1287
Last Page
1290
ISSN
2327-4662
Identifier
10.1109/JIOT.2018.2862381
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
ZHANG, Yinghui; SHU, Jiangang; LIU, Ximeng; LI, Jin; and ZHENG, Dong.
Security analysis of a large-scale concurrent data anonymous batch verification scheme for mobile healthcare crowd sensing. (2019). IEEE Internet of Things. 6, (1), 1287-1290.
Available at: https://ink.library.smu.edu.sg/sis_research/4152
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/JIOT.2018.2862381