Publication Type : Conference Paper
Publisher : Springer Nature Link
Source : Communications in Computer and Information Science
Url : https://link.springer.com/chapter/10.1007/978-3-030-95502-1_26
Campus : Coimbatore
School : School of Artificial Intelligence
Center : Center for Computational Engineering and Networking
Year : 2021
Abstract : Routing Protocol for Low Power and Lossy Networks (RPL) is a simple and lightweight routing protocol for Internet of Things (IoT). RPL-based IoT networks are prone to various security attacks because of their constrained nature. Black hole attack is one of the most destructive threats in RPL. This paper proposes INSULATE (IoT Network SecUrity in RPL using ANN based InTrusion Detection and Eviction), an Intrusion Detection System against black hole attack using Artificial Neural Network (ANN). The proposed IDS combines data from multiple watchdog nodes using Dempster-Shafer’s theory of evidence to estimate the likelihood of an attacker node. Experiments in real-world dataset shows that our proposed model exhibits a maximum detection rate of 99.23%, and achieves better network performance that is 1%–2% higher compared to existing techniques.
Cite this Research Publication : Prajisha, C., Vasudevan, A.R. (2022). An Intrusion Detection System for Blackhole Attack Detection and Isolation in RPL Based IoT Using ANN. In: Garg, D., Jagannathan, S., Gupta, A., Garg, L., Gupta, S. (eds) Advanced Computing. IACC 2021. Communications in Computer and Information Science, vol 1528. Springer, Cham. https://doi.org/10.1007/978-3-030-95502-1_26