arXiv (Cornell University) · 2018 · 40 citations · 12 references
Vehicle CommunicationEngineeringInformation SecurityAdvanced Driver-assistance SystemVehicular NetworksAutonomous SystemsHardware SecurityAutonomous VehiclesSystems EngineeringVehicle NetworkRapid PaceComputer EngineeringBrief SurveyAutomotive SecurityComputer ScienceAutonomous DrivingData SecurityCryptographyAutonomous Vehicle SoftwareAttack ModelCatastrophic ConsequencesAutomationControl System Security
Advanced driver assistance systems are advancing at a rapid pace and all major companies started investing in developing the autonomous vehicles. But the security and reliability is still uncertain and debatable. Imagine that a vehicle is compromised by the attackers and then what they can do. An attacker can control brake, accelerate and even steering which can lead to catastrophic consequences. This paper gives a very short and brief overview of most of the possible attacks on autonomous vehicle software and hardware and their potential implications.
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Robust Physical-World Attacks on Machine Learning Models.
Ivan Evtimov, Kevin Eykholt, Earlence Fernandes et al. · arXiv (Cornell University) · 2017 · 197 citations · Full text
Convolutional Neural Network, Engineering, Machine Learning +17
Security of Autonomous Systems Employing Embedded Computing and Sensors
Alexander M. Wyglinski, Xinming Huang, Lifeng Lai et al. · IEEE Micro · 2013 · 120 citations