Wonsuk Choi

Kyungho Joo, Wonsuk Choi, Dong Hoon Lee

Recently, the traditional way to unlock car doors has been replaced with a keyless entry system which proves more convenient for automobile owners. When a driver with a key fob is in the vicinity of the vehicle, doors automatically unlock on user command. However, unfortunately, it has been shown that these keyless entry systems are vulnerable to signal relaying attacks. While it is evident that automobile manufacturers incorporate preventative methods to secure these keyless entry systems, they continue to be vulnerable to a range of attacks. Relayed signals result in valid packets that are verified as legitimate, and this makes it is difficult to distinguish a legitimate door unlock request from a malicious signal. In response to this vulnerability, this paper presents an RF fingerprinting method (coined HOld the DOoR, HODOR) to detect attacks on keyless entry systems the first attempt to exploit the RF fingerprint technique in the automotive domain. HODOR is designed as a sub authentication method that supports existing authentication systems for keyless entry systems and does not require any modification of the main system to perform. Through a series of experiments, the results demonstrate that HODOR competently and reliably detects attacks on keyless entry systems. HODOR achieves both an average false positive rate (FPR) of 0.27 percent with a false negative rate (FNR) of 0 percent for the detection of simulated attacks, corresponding to current research on keyless entry car theft.

Wonsuk Choi, Hyo Jin Jo, Samuel Woo et al.

In the last several decades, the automotive industry has come to incorporate the latest Information and Communications (ICT) technology, increasingly replacing mechanical components of vehicles with electronic components. These electronic control units (ECUs) communicate with each other in an in-vehicle network that makes the vehicle both safer and easier to drive. Controller Area Networks (CANs) are the current standard for such high quality in-vehicle communication. Unfortunately, however, CANs do not currently offer protection against security attacks. In particular, they do not allow for message authentication and hence are open to attacks that replay ECU messages for malicious purposes. Applying the classic cryptographic method of message authentication code (MAC) is not feasible since the CAN data frame is not long enough to include a sufficiently long MAC to provide effective authentication. In this paper, we propose a novel identification method, which works in the physical layer of an in-vehicle CAN network. Our method identifies ECUs using inimitable characteristics of signals enabling detection of a compromised or alien ECU being used in a replay attack. Unlike previous attempts to address security issues in the in-vehicle CAN network, our method works by simply adding a monitoring unit to the existing network, making it deployable in current systems and compliant with required CAN standards. Our experimental results show that the bit string and classification algorithm that we utilized yielded more accurate identification of compromised ECUs than any other method proposed to date. The false positive rate is more than 2 times lower than the method proposed by P.-S. Murvay et al. This paper is also the first to identify potential attack models that systems should be able to detect.