Potential cyber threats of adversarial attacks on autonomous driving models
E Boltachev - Journal of Computer Virology and Hacking Techniques, 2023 - Springer
Abstract Autonomous Vehicles (CAVs) are currently seen as a viable alternative to
traditional vehicles. However, CAVs will face serious cyber threats because many …
traditional vehicles. However, CAVs will face serious cyber threats because many …
[PDF][PDF] Adversarial Attacks and Defense Technologies on Autonomous Vehicles: A Review.
In recent years, various domains have been influenced by the rapid growth of machine
learning. Autonomous driving is an area that has tremendously developed in parallel with …
learning. Autonomous driving is an area that has tremendously developed in parallel with …
Cybersecurity of autonomous vehicles: A systematic literature review of adversarial attacks and defense models
Autonomous driving (AD) has developed tremendously in parallel with the ongoing
development and improvement of deep learning (DL) technology. However, the uptake of …
development and improvement of deep learning (DL) technology. However, the uptake of …
A hybrid defense method against adversarial attacks on traffic sign classifiers in autonomous vehicles
Adversarial attacks can make deep neural network (DNN) models predict incorrect output
labels, such as misclassified traffic signs, for autonomous vehicle (AV) perception modules …
labels, such as misclassified traffic signs, for autonomous vehicle (AV) perception modules …
Towards autonomous driving model resistant to adversarial attack
KH Shibly, MD Hossain, H Inoue… - Applied Artificial …, 2023 - Taylor & Francis
ABSTRACT Connected and Autonomous Vehicles (CAVs) offer improved efficiency and
convenience through innovative embedded devices. However, the development of these …
convenience through innovative embedded devices. However, the development of these …
Attacks on machine learning: Adversarial examples in connected and autonomous vehicles
P Sharma, D Austin, H Liu - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
Connected and autonomous vehicles (CAV aka driverless cars) offset human response for
transportation infrastructure, enhancing traffic efficiency, travel leisure, and road safety …
transportation infrastructure, enhancing traffic efficiency, travel leisure, and road safety …
Adversarial attacks on traffic sign recognition: A survey
S Pavlitska, N Lambing… - 2023 3rd International …, 2023 - ieeexplore.ieee.org
Traffic sign recognition is an essential component of perception in autonomous vehicles,
which is currently performed almost exclusively with deep neural networks (DNNs) …
which is currently performed almost exclusively with deep neural networks (DNNs) …
Fast and Lightweight Vision-Language Model for Adversarial Traffic Sign Detection
Several attacks have been proposed against autonomous vehicles and their subsystems
that are powered by machine learning (ML). Road sign recognition models are especially …
that are powered by machine learning (ML). Road sign recognition models are especially …
Adaptive square attack: Fooling autonomous cars with adversarial traffic signs
To better understand the road condition and make correct driving decisions, traffic sign
recognition becomes a crucial component commonly equipped in the vision system of …
recognition becomes a crucial component commonly equipped in the vision system of …
Securing Autonomous Vehicles Visual Perception: Adversarial Patch Attack and Defense Schemes With Experimetal Validations
J Liang, R Yi, J Chen, Y Nie… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Autonomous vehicles (AVs) heavily depend on machine learning-based algorithms for the
purpose of environmental perception. However, extensively utilized deep learning-based …
purpose of environmental perception. However, extensively utilized deep learning-based …