A secure and effective biometric-based user authentication scheme for wireless sensor networks using smart card and fuzzy extractor.
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| Title: | A secure and effective biometric-based user authentication scheme for wireless sensor networks using smart card and fuzzy extractor. |
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| Authors: | Das, Ashok Kumar1 iitkgp.akdas@gmail.com |
| Source: | International Journal of Communication Systems. 1/10/2017, Vol. 30 Issue 1, pn/a-N.PAG. 25p. |
| Subjects: | Wireless sensor network access control, Biometry, Smart cards, Fuzzy systems, Computer security |
| Abstract: | User authentication is a prominent security requirement in wireless sensor networks (WSNs) for accessing the real-time data from the sensors directly by a legitimate user (external party). Several user authentication schemes are proposed in the literature. However, most of them are either vulnerable to different known attacks or they are inefficient. Recently, Althobaiti et al. presented a biometric-based user authentication scheme for WSNs. Although their scheme is efficient in computation, in this paper, we first show that their scheme has several security pitfalls such as (i) it is not resilient against node capture attack; (ii) it is insecure against impersonation attack; and (iii) it is insecure against man-in-the-middle attack. We then aim to propose a novel biometric-based user authentication scheme suitable for WSNs in order to withstand the security pitfalls found in Althobaiti et al. scheme. We show through the rigorous security analysis that our scheme is secure and satisfies the desirable security requirements. Furthermore, the simulation results for the formal security verification using the most widely used and accepted Automated Validation of Internet Security Protocols and Applications tool indicate that our scheme is secure. Our scheme is also efficient compared with existing related schemes. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Communication Systems is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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