IDS for In-vehicle Network

Today's cars have a complex in-vehicle network and millions lines of code that control almost every function in the vehicle, including the safety critical functions. The in-vehicle networks are vulnerable and security threats against them have proved to affect the safety of passengers. To counter these vulnerabilities, different security solutions have been proposed.  In this short paper, we study two recently proposed anomaly-based Intrusion Detection Systems (IDS) that adopt deep neural network and ECU fingerprinting for attack detection.

Introductory papers

Kleberger et.al: Security aspects of the in-vehicle network in the connected car (IV 2011)

Advanced papers

K.-T. Cho and K. G. Shin: Fingerprinting electronic control units for vehicle intrusion detection (USENIX Security 16)

M.-J. Kang and J.-W. Kang: A Novel Intrusion Detection Method Using Deep Neural Network for In-Vehicle Network Security (VTC 2016)