Review of Secure Communication Approaches for In-Vehicle Network

Hu, Qiang; Luo, Feng

doi:10.1007/s12239-018-0085-1

Cited by 49 publications

(20 citation statements)

References 22 publications

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“…Unfortunately, the MAC schemes presented in the existing literature fail to address these challenges comprehensively. Hence, these schemes are either not secure or impractical to implement with the existing CAN [16], [19].…”

Section: Comparison With Other Potential Defensesmentioning

confidence: 99%

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Evading Voltage-Based Intrusion Detection on Automotive CAN

Bhatia

Kumar

Serag

et al. 2021

Proceedings 2021 Network and Distributed System Security Symposium

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works/nodes through USB, cellular, Bluetooth, and WiFi connections [48]. Unfortunately, these interfaces provide various attack surfaces making these ECUs vulnerable to a remote adversary [6], [31], [32], [35], [36]. After infiltrating CAN by compromising any of these ECUs, the adversary can carry out a variety of attacks [24], [32], [35], [36], [49] against other ECUs since the CAN lacks mainstream network security capabilities due to resource constraints. In particular, a compromised ECU (e.g., Telematics Control Unit) may impersonate a benign ECU (e.g., Engine Control Unit) that cannot be remotely compromised, and forge the latter's CAN messages to disrupt safety-critical automotive functions (e.g., engine speed). We call such attacks ECU masquerade attacks.

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Section: Comparison With Other Potential Defensesmentioning

confidence: 99%

“…Various cryptographic solutions [16], [19] have been proposed to secure CAN by authenticating message payloads. Unfortunately, cryptographic solutions remain impractical as vehicular CAN employs resource-constrained ECUs and remains bandwidth-constrained.…”

Section: Defensementioning

confidence: 99%

Evading Voltage-Based Intrusion Detection on Automotive CAN

Bhatia

Kumar

Serag

et al. 2021

Proceedings 2021 Network and Distributed System Security Symposium

View full text Add to dashboard Cite

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“…In-vehicle network (IVN) protocols such as controller area network (CAN), local interconnect network (LIN), and FlexRay have been employed to accommodate various requirements for data exchange between electronic control units (ECUs) [1][2][3]. However, existing IVN protocols are showing their technical limitations as vehicles tend to be smarter by employing advanced driver assistance systems (ADAS), vehicle-to-everything (V2X), and autonomous driving.…”

Section: Introductionmentioning

confidence: 99%

Development of an Ethernet-Based Heuristic Time-Sensitive Networking Scheduling Algorithm for Real-Time In-Vehicle Data Transmission

et al. 2021

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The rapid development and adaptation of advanced driver assistance systems (ADAS) and autonomous driving increases the burden of in-vehicle networks. In-vehicle networks are now required to provide a fast data rate and bounded delay for real-time operation, while conventional protocols such as controller area networks, local interconnected networks, and FlexRay begin to show limitations. Ethernet-based time-sensitive network (TSN) technology has been proposed as an alternative. TSN is a set of Ethernet standards being developed by the IEEE TSN task group, which aims to satisfy requirements such as real-time operation, stability, and low and bounded latency, and it can be used in automotive, industrial, and aerospace applications. This study introduces several standards for Ethernet traffic scheduling based on TSN technology and proposes a heuristic-based scheduling algorithm for Ethernet scheduling. In addition, three network configurations are simulated using OMNeT++ to show the applicability. The heuristic TSN scheduling algorithm is a straightforward and systematic procedure for practical network designers.

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“…This term symbolizes the application of technologies from various fields to automobiles [1][2][3]. Considerable effort has also been directed toward improving driving stability and convenience by utilizing various vehicle technologies, such as sensors and wired/wireless communications [4][5][6]. Tires, which are in direct contact with the road surface, greatly affect the stability of the vehicle.…”

Section: Introductionmentioning

confidence: 99%

A Road Condition Classification Algorithm for a Tire Acceleration Sensor using an Artificial Neural Network

et al. 2020

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The automotive industry is experiencing a period of innovation, represented by the term CASE (connected, autonomous, shared, and electric). Among the innovative new technologies for automobiles, intelligent tire (iTire) collects road surface information through sensors installed inside a tire and informs the driver of the road conditions. iTire can promote safe driving. Various kinds of research on iTire is ongoing, and this paper proposes an algorithm to determine the road surface conditions while driving. Specifically, we have proposed a method for extracting the feature points of a frequency band, by converting acceleration data collected by sensors through fast Fourier transform (FFT) and determining road surface conditions via an artificial neural network. Lastly, the applicability of the algorithm was verified.

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Review of Secure Communication Approaches for In-Vehicle Network

Cited by 49 publications

References 22 publications

Evading Voltage-Based Intrusion Detection on Automotive CAN

Evading Voltage-Based Intrusion Detection on Automotive CAN

Development of an Ethernet-Based Heuristic Time-Sensitive Networking Scheduling Algorithm for Real-Time In-Vehicle Data Transmission

A Road Condition Classification Algorithm for a Tire Acceleration Sensor using an Artificial Neural Network

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