Biblio

Nowadays, the growing need to connect modern vehicles through computer networks leads to increased risks of cyberattacks. The internal network, which governs the several electronic components of a vehicle, is becoming increasingly overexposed to external attacks. The Controller Area Network (CAN) protocol, used to interconnect those devices is the key point of the internal network of modern vehicles. Therefore, securing such protocol is crucial to ensure a safe driving experience. However, the CAN is a standard that has undergone little changes since it was introduced in 1983. More precisely, in an attempt to reduce latency, the transfer of information remains unencrypted, which today represents a weak point in the protocol. Hence, the need to protect communications, without introducing low-level alterations, while preserving the performance characteristics of the protocol. In this work, we investigate the possibility of using symmetric encryption algorithms for securing messages exchanged by CAN protocol. In particular, we evaluate the using of lightweight ciphers to secure CAN-level communication. Such ciphers represent a reliable solution on hardware-constrained devices, such as microcontrollers.

The presence of security vulnerabilities in automotive networks has already been shown by various publications in recent years. Due to the specification of the Controller Area Network (CAN) as a broadcast medium without security mechanisms, attackers are able to read transmitted messages without being noticed and to inject malicious messages. In order to detect potential attackers within a network or software system as early as possible, Intrusion Detection Systems (IDSs) are prevalent. Many approaches for vehicles are based on techniques which are able to detect deviations from specified CAN network behaviour regarding protocol or payload properties. However, it is challenging to detect attackers who secretly connect to CAN networks and do not actively participate in bus traffic. In this paper, we present an approach that is capable of successfully detecting unknown CAN devices and determining the distance (cable length) between the attacker device and our sensing unit based on Time Domain Reflectometry (TDR) technique. We evaluated our approach on a real vehicle network.