An Efficient Wireless Sensor Network based Intrusion Detection System
subject: IDS; machine learning; responsive mechanism; Spectral clustering; WSN
description: Wireless Sensor Networks (WSNs) are widely used in diverse applications due to their cost-effectiveness and versatility. However, they face substantial difficulties because of their innate resource constraints and susceptibility to security attacks. A possible method to improve the security of WSNs is clustering-based intrusion detection and responding mechanisms. An in-depth analysis of the clustering-based intrusion detection and response method for WSNs is presented in this study. The suggested method efficiently uses data mining and machine learning techniques to identify unusual behaviour and probable intrusions. The system effectively analyses data inside clusters by grouping Sensor Nodes (SN) into clusters, allowing it to differentiate between legitimate patterns and insecure activity. The network may respond promptly to identified breaches and react to the responsive mechanism, which reduces their impact and protects network integrity. The proposed Mathematically Modified Gene Populated Spectral Clustering Based Intrusion Detection System and Responsive Mechanism (MMMMGPSC-IDS-RM) is compared with existing state-of-art techniques, and MMMMGPSC-IDS-RM outperforms with the highest detection rate of 96%. 2023 IEEE.
creator: Rajassekharan D.; Ramachandran V.; Sharma D.K.; Palanisamy T.; Myilsam Y.V.; Poonia R.C.
source: 2023 International Conference on Communication, Security and Artificial Intelligence, ICCSAI 2023, pp. 444-449.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2023-01-01
rights: Restricted Access
relation: ISBN: 979-835036996-0
format: Online
language: English
type: Conference paper
coverage: Rajassekharan D., Peninsula College, Faculty of Computer Science, Malaysia; Ramachandran V., Gitam School of Computing, Gitam Deemed to Be University, Department of Computer Science and Engineering, Bengaluru, 561203, India; Sharma D.K., Jaypee University of Engineering and Technology, Department of Mathematics, Madhya Pradesh, Guna, 473226, India; Palanisamy T., Nandha Engineering College, Department of Computer Science and Engineering, Tamil Nadu, Erode, India; Myilsam Y.V., V.S.B College of Engineering, Department of Electrical and Electronics Engineering, Technical Campus, Tamil Nadu, Coimbatore, 642109, India; Poonia R.C., Christ (Deemed to Be University), Department of Computer Science, Delhi-NCR, Uttar Pradesh, Ghaziabad, 201003, India