Hybrid Pigeon Inspired Optimizer-Gray Wolf Optimization for Network Intrusion Detection
Journal of System and Management Sciences · 2022
The physical objects like smart home appliances many more are present in the Internet of Things (IoT).The network has an assigned Internet Address (IP) uniquely that communicates through the external entities of user from a smart home in a network for exchange in data via internet.The IoT devices face an issue that are increased rapidly due to intruders or attackers such as Distributed Denial-of-Service (DDoS) attacks occurring at IoT environment.It has occurred due to the strong and security monitoring protection techniques.Thus, it is important for providing security during IoT attack detection.The hybrid optimization approach was used that is a combination of Pigeon Inspired Optimizer (PIO) and Gray Wolf Optimization (GWO) that is developed for detecting intrusion attacks.The Cosine-Similarity fitness function selects an optimal value during feature selection and the features are fed for the Multi-Support Vector Machine (M-SVM) for the attacks classification.Finally, results showed that the proposed hybrid PIO-GWO obtained better accuracy of 96.94 % better than the existing ensemble learning model of 96 %.