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Zhong, Sheng, Ren, Wei, Zhu, Tianqing, Ren, Yi 
ORCID: https://orcid.org/0000-0001-7423-6719 and Choo, Kim-Kwang Raymond
(2018)
Performance and security evaluations of identity-and pairing-based digital signature algorithms on Windows, Android, and Linux platforms: Revisiting the algorithms of Cha and Cheon, Hess, Barreto, Libert, McCullagh and Quisquater, and Paterson and Schuldt.
IEEE Access, 6.
pp. 37850-37857.
ISSN 2169-3536
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Abstract
Bilinear pairing, an essential tool to construct-efficient digital signatures, has applications in mobile devices and other applications. One particular research challenge is to design cross-platform security protocols (e.g. Windows, Linux, and other popular mobile operating systems) while achieving an optimal security-performance tradeoff. That is, how to choose the right digital signature algorithm, for example, on mobile devices while considering the limitations on both computation capacity and battery life. In this paper, we examine the security-performance tradeoff of four popular digital signature algorithms, namely: CC (proposed by Cha and Cheon in 2003), Hess (proposed by Hess in 2002), BLMQ (proposed by Barreto et al. in 2005), and PS (proposed by Paterson and Schuldt in 2006), on various platforms. We empirically evaluate their performance using experiments on Windows, Android, and Linux platforms, and find that BLMQ algorithm has the highest computational efficiency and communication efficiency. We also study their security properties under the random oracle model and assuming the intractability of the CDH problem, we reveal that the BLMQ digital signature scheme satisfies the property of existential unforgeable on adaptively chosen message and ID attack. The efficiency of PS algorithm is lower, but it is secure under the standard model.
| Item Type: | Article |
|---|---|
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Smart Emerging Technologies Faculty of Science > Research Groups > Data Science and AI |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 31 Jul 2018 09:30 |
| Last Modified: | 10 Dec 2024 01:31 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/67889 |
| DOI: | 10.1109/ACCESS.2018.2853703 |
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