CANTXSec: A Deterministic Intrusion Detection and Prevention System for CAN Bus Monitoring ECU Activations


연구 분야: Strategies



학회: International Conference on Applied Cryptography and Network Security


초록

Despite being a legacy protocol with various known security issues, Controller Area Network (CAN) still represents the de-facto standard for communications within vehicles, ships, and industrial control systems. Many research works have designed Intrusion Detection Systems (IDSs) to identify attacks by training machine learning classifiers on bus traffic or its properties. Actions to take after detection are, on the other hand, less investigated, and prevention mechanisms usually include protocol modification (e.g., adding authentication). An effective solution has yet to be implemented on a large scale in the wild. The reasons are related to the effort to handle sporadic false positives, the inevitable delay introduced by authentication, and the closed-source automobile environment that does not easily permit modifying Electronic Control Units (ECUs) software. In this paper, we propose CANTXSec, the first deterministic Intrusion Detection and Prevention system based on physical ECU activations. It employs a new classification of attacks based on the attacker’s need in terms of access level to the bus, distinguishing between Frame Injection Attacks (FIAs) (i.e., using frame-level access) and Single-Bit Attacks (SBAs) (i.e., employing bit-level access). CANTXSec detects and prevents classical attacks in the CAN bus, while detecting advanced attacks that have been less investigated in the literature. We prove the effectiveness of our solution on a physical testbed, where we achieve 100% detection accuracy in both classes of attacks while preventing 100% of FIAs. Moreover, to encourage developers to employ CANTXSec, we discuss implementation details, providing an analysis based on each user’s risk assessment.


Author Profile
Denis Donadel

University of Padova Padua Italy

Italy
Author Profile
Kavya Balasubramanian

University of Washington Seattle USA

United States
Author Profile
Alessandro Brighente

University of Padova Padua Italy

Italy

📄 논문 정보

발행 연도 2025년
인용수 0
출판 국가 Italy, United States
사이트 Springer
좋아요 수 0

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