Artificial bee colony method for identifying eavesdropper in terrestrial cellular networks. Issue 7 (7th April 2020)

• Record Type: Journal Article
• Authors: Udaya Suriya Rajkumar, D.; Gavaskar, P. Sunil; Al‐Turjman, Fadi; Sathiyaraj, R.; Balusamy, Balamurugan
• Is Part Of: Transactions on emerging telecommunications technologies. Volume 32:Issue 7(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-04-07
• Subjects: Telecommunication -- Periodicals; 384.05
• DOI: 10.1002/ett.3941
• Languages: English
• ISSNs: 2161-5748

Abstract

Abstract: Nowadays, with the extensive variety of uses of the terrestrial cellular network, the security requirement for these networks is expanding enormously. Although these networks have faced various attacks, the eavesdropper is the most remarkable one. In this attack, once in a while, the foe node postures itself as a bogus base station (BS) and obtains information from achieving the main BS or changes the obtained information. In this article, a well‐organized swarm intelligence approach is proposed within the context of agent‐based models to recognize eavesdroppers, and artificial bee colony attack detection can distinguish the eavesdropper with regard to the node IDs characterized in the rule_set. The nodes that create a caution on distinguishing an intruder are assembled collectively. To recognize the intruder, a voting method is projected. Artificial bee colony Boolean sign generation is projected, which is distributed to the cautioned nodes in the grouping, the keys for sign the expect list to consent on the intruder. The proposed techniques recognize the aberrant relations without producing false positives and limit the capacity in the nodes of the terrestrial network, in contrast with Intrusion Detection Architecture, for the identification of eavesdroppers. Abstract : Artificial Bee Colony Method for Identifying Eavesdropper in Terrestrial Cellular Networks.