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The Internet of Vehicle (IoV) is a technology that connects vehicles such as cars and buses to the internet. It facilitates the exchange of information between these vehicles for increased safety, efficiency, and speed. The IoV architecture consists of three layers: perception, network, and application. The main challenge in the design of IoT is the security issue. To handle the security issue we proposed an Intrusion Detection System (IDS) that uses deep learning models, specifically deep neural networks, to identify malicious network traffic and to classify the type of attack. The system operates in two stages: in the first stage, normal and attack traffic are differentiated, and in the second stage, the type of attack is determined. Three variants of rule extraction methods are proposed here including homogeneous methods using either decompositional or pedagogical rule extraction in both stages, and a heterogeneous …