The IDS ensures the security level of a vehicular communication system by detecting illegal activities based on the pre-trained data automatically. The IDS exploits machine learning models to predict, identify, and classify malicious behaviors. Most VANET-IDS strategies employ fundamental machine learning algorithms for detection and classification. The machine learning-based IDS are promising solutions to handle the security issues with abundant VANET data. The performance of machine learning models mainly depends on the dataset selection. Efficient dataset selection is a challenging task in the current vehicular system. The collaborative machine learning-based IDS models are widely exploited in VANET for security and performance enhancement.