References of "Castignani, German"
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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 detailCANMatch: A Fully Automated Tool for CAN Bus Reverse Engineering based on Frame Matching
Buscemi, Alessio UL; Turcanu, Ion; Castignani, German et al

in IEEE Transactions on Vehicular Technology (2021)

Controller Area Network (CAN) is the most frequently used in-vehicle communication system in the automotive industry today. The communication inside the CAN bus is typically encoded using proprietary ... [more ▼]

Controller Area Network (CAN) is the most frequently used in-vehicle communication system in the automotive industry today. The communication inside the CAN bus is typically encoded using proprietary formats in order to prevent easy access to the information exchanged on the bus. However, it is still possible to decode this information through reverse engineering, performed either manually or via automated tools. Existing automated CAN bus reverse engineering methods are still time-consuming and require some manual effort, i.e., to inject diagnostic messages in order to trigger specific responses. In this paper, we propose CANMatch a fully automated CAN bus reverse engineering framework that does not require any manual effort and significantly decreases the execution time by exploiting the reuse of CAN frames across different vehicle models. We evaluate the proposed solution on a dataset of CAN logs, or traces, related to 479 vehicles from 29 different automotive manufacturers, demonstrating its improved performance with respect to the state of the art. [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 ▲]

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See detailEnabling vehicular mobility in city-wide IEEE 802.11 networks through predictive handovers
Mouton, Maximilien; Castignani, German; Frank, Raphaël UL et al

in Vehicular Communications (2015), 2(2), 59-69

Detailed reference viewed: 144 (2 UL)