LLAKEP: A Low-Latency Authentication and Key Exchange Protocol for Energy Internet of Things in the Metaverse Era

Xin Zhang, Xin Huang, Haotian Yin, Jiajia Huang, Sheng Chai, Bin Xing, Xiaohua Wu and Liangbin Zhao
Additional contact information
Xin Zhang: College of Data Science, Taiyuan University of Technology, Taiyuan 030024, China
Xin Huang: College of Data Science, Taiyuan University of Technology, Taiyuan 030024, China
Haotian Yin: College of Data Science, Taiyuan University of Technology, Taiyuan 030024, China
Jiajia Huang: College of Data Science, Taiyuan University of Technology, Taiyuan 030024, China
Sheng Chai: College of Data Science, Taiyuan University of Technology, Taiyuan 030024, China
Bin Xing: College of Data Science, Taiyuan University of Technology, Taiyuan 030024, China
Xiaohua Wu: China Tower, Taiyuan 030001, China
Liangbin Zhao: China Tower, Taiyuan 030001, China

Mathematics, 2022, vol. 10, issue 14, 1-21

Abstract: The authenticated key exchange (AKE) protocol can ensure secure communication between a client and a server in the electricity transaction of the Energy Internet of things (EIoT). Park proposed a two-factor authentication protocol 2PAKEP, whose computational burden of authentication is evenly shared by both sides. However, the computing capability of the client device is weaker than that of the server. Therefore, based on 2PAKEP, we propose an authentication protocol that transfers computational tasks from the client to the server. The client has fewer computing tasks in this protocol than the server, and the overall latency will be greatly reduced. Furthermore, the security of the proposed protocol is analyzed by using the ROR model and GNY logic. We verify the low-latency advantage of the proposed protocol through various comparative experiments and use it for EIoT electricity transaction systems in a Metaverse scenario.

Keywords: EIoT; low-latency; AKE; security analysis; ROR; GNY logic; metaverse (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/14/2545/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/14/2545/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:14:p:2545-:d:868409

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().