A stacked ensemble learning IDS model for Software-defined VANET. (arXiv:2312.04956v3 [cs.CR] UPDATED)

Intrusion Detection Systems (IDS) are widely employed to detect and mitigate
external network security events. VANETs (Vehicle ad-hoc Networks) are
evolving, especially with the development of Connected Autonomous Vehicles
(CAVs). So, it is crucial to assess how traditional IDS approaches can be
utilised for emerging technologies. To address this concern, our work presents
a stacked ensemble learning approach for IDS, which combines multiple machine
learning algorithms to detect threats more effectively than single algorithm
methods. Using the CICIDS2017 and the …

address autonomous autonomous vehicles connected defined detect detection development emerging events external ids intrusion intrusion detection network networks network security security security events software systems technologies vehicle vehicles