Autonomous detection of malevolent nodes using secure heterogeneous cluster protocol. (May 2022)

• Record Type: Journal Article
• Authors: Kotteeswaran, C.; Patra, Indrajit; Nagaraju, Regonda; Sungeetha, D.; Kommula, Bapayya Naidu; Algani, Yousef Methkal Abd; Murugavalli, S.; Bala, B. Kiran
• Is Part Of: Computers & electrical engineering. Volume 100(2022)
• Publication Date: 2022-05
• Subjects: Security -- Malicious nodes -- Wireless Sensor Networks -- Autonomous detection; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2022.107902
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: The main objective of the research work is focused on autonomous detection of malevolent nodes. The identification of false information is performed through secure heterogeneous cluster protocol in Wireless Sensor Networks. The performance parameters are evaluated to attain high accuracy rate of detection process. Abstract: Surfing of internet by the users has been more vital from the inception of the network. However, the number of users using the internet is increasing gradually. As a result, it has also become a serious threat to users who are using the internet because due to the false information and security threat by malicious users. In this context, it is vital to provide the trusted information to the users. In order to achieve the same, the Heterogeneous Cluster-Based Secure Protocol (HCBSP) can be used to detect the malicious nodes and thereby, to provide a secure path for data transmission. Initially, the nodes are deployed, then clusters are formed and subsequently, the data are transmitted between cluster and base. The HCBSP operates over the cluster for effective attack detection and secures the data transmission in wireless network. This performance is evaluated and compared with the existing methods. Here, the result shows that the HCBSP is the most effective platform in detecting the malicious nodes with high accuracy rate. Graphical abstract: Image, graphical abstract