Artificial neural network and symmetric key cryptography based verification protocol for 5G enabled Internet of Things. Issue 10 (23rd August 2022)

• Record Type: Journal Article
• Authors: Nyangaresi, Vincent Omollo; Ahmad, Musheer; Alkhayyat, Ahmed; Feng, Wei
• Other Names: Dhiman Gaurav guestEditor.; Nagar Atulya K. guestEditor.; Gupta Deepak guestEditor.
• Is Part Of: Expert systems. Volume 39:Issue 10(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-08-23
• Subjects: 5G -- ANN -- authentication -- BAN logic -- internet of things -- security; Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.13126
• Languages: English
• ISSNs: 0266-4720

Abstract

Abstract: Driven by the requirements for entirely low communication latencies, high bandwidths, reliability and capacities, the Fifth Generation (5G) networks has been deployed in a number of countries. One of the most prevalent application scenarios of 5G networks is the Internet of Things (IoT) that can potentially boost convenience and energy savings. However, the information exchanged over the open wireless 5G networks is susceptible to numerous attacks such as malicious modifications. Although many protocols have been developed to protect against these attacks, the provision of optimum security and privacy issues in 5G networks is still an open challenge. This is attributed to the high device density, frequent handovers and resource constrained nature the 5G IoT nodes. In this article, a network selection and authentication protocol that securely verifies the authenticity of all the communicating entities is presented. The network selection is accomplished using Artificial Neural Network (ANN) for increased efficiency. In addition, all the security tokens are independently derived at the end devices without the involvement of any central authority. Formal security analysis based on the Burrows–Abadi–Needham (BAN) logic shows that all the terminals securely authenticate each other before the onset of packet exchanges. In addition, it is shown that this protocol thwarts majority of the conventional 5G attack vectors and is robust under the Dolev–Yao (DY) threat model. Moreover, a comparison with other related schemes shows that the proposed protocol offers many adorable security features at relatively low communication and computation costs. The simulation results show that the deployed ANN yields low packet loss ratio and latency variations.