Lookup NU author(s): Professor Gui Yun Tian,
Dr Bin Gao
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
© 2018 Springer Science+Business Media, LLC, part of Springer Nature WSNs are one of the important components in the Internet of Things (IoTs), since they enable gathering and transmitting of data to the cloud server via the Internet medium. Designing an efficient secure cryptography scheme for the IoTs is a challenging task, since sensor node is a resource-constrained device. In this paper, an authentication key agreement scheme is proposed to build a secure channel between WSNs and a cloud server in the IoTs. The proposed scheme has two properties: (1) it has a lightweight computation, and (2) it provides various security properties of key agreement. In addition, it is proven to be secure under computation Diffe–Hellman assumption in the random oracle model. AKAIoTs is implemented using Contiki OS and use Z1 emulator to evaluate time overhead and memory usage. Three different curves; “BN-P158”, “SECG-P160” and “NIST-P192” are used. The implementation results verify that, the proposed scheme is computationally efficient and memory usage between 51 and 52% from total memory of ROM, and between 59 and 62% from total memory of RAM for three different security levels. As a result, curve SECG-P160 might be a good choice to supply security for the IoTs devices, since it consumes reasonable time which result in less power consumption than curve NIST-P192 and more secure than curve BN-P158. Compared with existing relevant schemes, the proposed AKAIoTs is efficient in terms of energy consumption. Moreover, two application scenarios are given to show how the proposed scheme can be applied in the IoTs applications.
Author(s): Saeed MES, Liu Q-Y, Tian G, Gao B, Li F
Publication type: Article
Publication status: Published
Journal: Wireless Networks
Print publication date: 01/08/2019
Online publication date: 10/03/2018
Acceptance date: 02/04/2016
ISSN (print): 1022-0038
ISSN (electronic): 1572-8196
Publisher: Springer New York LLC
Altmetrics provided by Altmetric