Integration of Machine Learning Algorithm into IDS-ATiC-AODV (Improved Data Security - Avoid Time Complexity Ad-Hoc On-Demand Distance Vector) Routing Protocol - Kanimozhi, N; Ganesh, S Hari; Karthikeyan, B (International Journal of Computer Sciences and Engineering, 2024)
The Mobile Ad-Hoc Network presents a remarkable infrastructure-free approach for information exchange between source and destination utilizing intermediate nodes. It offers robust security features and tackles time complexity through its routing protocols. In the author`s prior research, solutions were proposed for approximately eight qualitative and quantitative Quality of Service (QoS) metrics, along with a reduction in solution algorithm execution time. These solutions were automated using Machine Learning (ML) algorithms, leveraging a dataset named Infra-Less KMS and an optimal algorithm, Support Vector Machine (SVM) & Gaussian mixture model (GMM) identified in previous works. In this study, the IDS-ATiC AODV Solution algorithm will be implemented using SVM, with a focus on evaluating prediction accuracy.