Wireless Networks

, Volume 25, Issue 6, pp 3081–3101 | Cite as

AKAIoTs: authenticated key agreement for Internet of Things

  • Mutaz Elradi S. SaeedEmail author
  • Qun-Ying Liu
  • GuiYun Tian
  • Bin Gao
  • Fagen Li


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.


Wireless sensor network (WSNs) Elliptic curve cryptography (ECC) Identity-based Authenticated key establishment (AKE) Internet of Things (IoTs) 



The authors would like to thank NSFC (No. 51677020), Xihua University Project (No. szjj2016-093) and FP7 through CONHEALTH project partially funding the research.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Mutaz Elradi S. Saeed
    • 1
    • 2
    Email author
  • Qun-Ying Liu
    • 1
    • 2
  • GuiYun Tian
    • 1
    • 2
  • Bin Gao
    • 1
    • 2
  • Fagen Li
    • 1
  1. 1.School of Automation EngineeringUniversity of Electronic Science and Technology of ChinaChengduChina
  2. 2.School of EngineeringNewcastle UniversityNewcastle upon TyneUK

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