References of "Buscemi, Alessio 50027601"
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See detailOn Frame Fingerprinting and Controller Area Networks Security in Connected Vehicles
Buscemi, Alessio UL; Turcanu, Ion; Castignani, German et al

in IEEE Consumer Communications & Networking Conference, Virtual Conference 8-11 January 2022 (2022, January)

Modern connected vehicles are equipped with a large number of sensors, which enable a wide range of services that can improve overall traffic safety and efficiency. However, remote access to connected ... [more ▼]

Modern connected vehicles are equipped with a large number of sensors, which enable a wide range of services that can improve overall traffic safety and efficiency. However, remote access to connected vehicles also introduces new security issues affecting both inter and intra-vehicle communications. In fact, existing intra-vehicle communication systems, such as Controller Area Network (CAN), lack security features, such as encryption and secure authentication for Electronic Control Units (ECUs). Instead, Original Equipment Manufacturers (OEMs) seek security through obscurity by keeping secret the proprietary format with which they encode the information. Recently, it has been shown that the reuse of CAN frame IDs can be exploited to perform CAN bus reverse engineering without physical access to the vehicle, thus raising further security concerns in a connected environment. This work investigates whether anonymizing the frames of each newly released vehicle is sufficient to prevent CAN bus reverse engineering based on frame ID matching. The results show that, by adopting Machine Learning techniques, anonymized CAN frames can still be fingerprinted and identified in an unknown vehicle with an accuracy of up to 80 %. [less ▲]

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See detailA Data-Driven Minimal Approach for CAN Bus Reverse Engineering
Buscemi, Alessio UL; Castignani, German; Engel, Thomas UL et al

in 3rd IEEE Connected and Automated Vehicles Symposium, Victoria, Canada, 4-5 October 2020 (2020)

Current in-vehicle communication systems lack security features, such as encryption and secure authentication. The approach most commonly used by car manufacturers is to achieve security through obscurity ... [more ▼]

Current in-vehicle communication systems lack security features, such as encryption and secure authentication. The approach most commonly used by car manufacturers is to achieve security through obscurity – keep the proprietary format used to encode the information secret. However, it is still possible to decode this information via reverse engineering. Existing reverse engineering methods typically require physical access to the vehicle and are time consuming. In this paper, we present a Machine Learning-based method that performs automated Controller Area Network (CAN) bus reverse engineering while requiring minimal time, hardware equipment, and potentially no physical access to the vehicle. Our results demonstrate high accuracy in identifying critical vehicle functions just from analysing raw traces of CAN data. [less ▲]

Detailed reference viewed: 231 (15 UL)