Machine Learning for Automotive Security in Technology Transfer

The new breed of vehicles comes stashed with cutting-edge technologies. The in-vehicle communication system (CAN Bus) smartly connects to all such Electronic Control Units (ECU) to enhance the safety, security, and stability of the vehicle, driver, and passengers. We need efficient and real-time Intrusion Detection Systems (IDS) to prevent threats in vehicles. Extensive research about IDS on CAN bus have been proposed, but most are offline. Further, the in-vehicle ECUs need to be more robust for implementing IDS. This paper presents an in-vehicle multi-class IDS aiming to detect cyber attacks in real-time. The goal is to transfer this technology to Automotive Industry in order to increase the safety and security of vehicles, drivers, and passengers.