Security and Privacy Vulnerabilities of In-Car Wireless Networks: A Tire Pressure Monitoring System Case Study

By Ishtiaq Rouf, Robert D. Miller, H. Mustafa, Travis Taylor, Sangho Oh, Wenyuan Xu, Marco Gruteser, Wade Trappe, I. Seskar. USENIX Security Symposium, 2010

451 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e48cc909e4c3bc1be0860698dbced41d3e07c3ab

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Citations in the corpus

Comprehensive Experimental Analyses of Automotive Attack Surfaces (2011, background): “’s recent analysis of the wireless Tire Pressure Monitoring System (TPMS) in a modern vehicle [22].”
Remote Attacks on Automated Vehicles Sensors : Experiments on Camera and LiDAR (2015, background): “Fourthly, attacks on TPMS [31] and GNSS [4] have already been demonstrated in real experiments.”
Potential Cyberattacks on Automated Vehicles (2015, background): “The limitations of autonomous automated vehicles include the limited line-of-sight and that it could not “see-through” objects/corners.”
Cyber Threats Facing Autonomous and Connected Vehicles: Future Challenges (2017, methodology): “[29] suggest that asymmetric encryption can be used as a potential mitigation technique.”
DolphinAttack: Inaudible Voice Commands (2017, background): “investigate and classify sensor spoofing attacks [46] into three categories: regular channel attacks (replay attack) [19, 26, 66], transmission channel attacks, and side channel attacks [11, 14, 15, 47, 49].”
Pseudonym Schemes in Vehicular Networks: A Survey (2015, background): “of pseudonym change—which is easy to assess—tracking becomes trivial [103].”
Intrusion detection system based on the analysis of time intervals of CAN messages for in-vehicle network (2016, background): “introduced vulnerabilities of in-vehicle wireless networks through the case study of pressure monitoring system [7].”
Adversarial Sensor Attack on LiDAR-based Perception in Autonomous Driving (2019, background): “showed that tire pressure sensors are vulnerable to wireless jamming and spoofing attacks [43].”
Multi-Factor Authentication: A Survey (2018, background): “Validating the identity of the user and the electronic device (or its system) [55,56]; • Validating the infrastructure connection [57]; • Validating the interconnected IoT devices, such as a smartphone, tablet, wearable device, or any other digital token (key dongle) [58].”
A Survey of Intrusion Detection for In-Vehicle Networks (2020, background): “Rouf et al. realized the reorganization of the message by the TPMS [28].”
A Survey of Physics-Based Attack Detection in Cyber-Physical Systems (2018, background): “There is a growing literature on the security of Cyber-Physical Systems (CPS), including the verification of control code by an embedded system before it reaches the Programmable Logic Controller (PLC), Remote Terminal Unit (RTU), or Intelligent Electronic Device (IED) [69], security of embedded dev”
Intra-Vehicle Networks: A Review (2015, background): “[4] raised concerns about security in wireless networks, demonstrating that eavesdropping on a TPMS network, and even reverse engineering and injecting false data,”
Cyber-Physical Systems Security—A Survey (2017, unknown): “Compromising the CPS’s conﬁdentiality, integrity, availability, privacy, or safety.”
Entropy-based anomaly detection for in-vehicle networks (2011, background): “Previous research regarding in-vehicle networks has mainly focused on safety issues [12], more recent activities go beyond and consider IT security aspects as well [16], [19].”