Paper Title: Machine Learning Algorithms for Detecting Intra-Vehicular Data Falsification
Conference Name: KICS SUMMER 2024
Abstract: The Internet of Vehicles (IoV) emphasizes the crucial role of Intrusion Detection Systems (IDS) in strengthening security with Machine learning (ML) algorithms, promising enhanced IDS performance by offering real-time anomaly detection capabilities. This study evaluates ML algorithms for accurately detecting intra-vehicular data falsification. Combining effective data preprocessing, the simulation results demonstrate enhanced ML model performance in notably detecting intrusions leveraging the recently published CICIoV2024 dataset.