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 …
An analysis of adversarial attacks and defenses on autonomous driving models
Nowadays, autonomous driving has attracted much attention from both industry and
academia. Convolutional neural network (CNN) is a key component in autonomous driving …
academia. Convolutional neural network (CNN) is a key component in autonomous driving …
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 …
Deep learning-based autonomous driving systems: A survey of attacks and defenses
The rapid development of artificial intelligence, especially deep learning technology, has
advanced autonomous driving systems (ADSs) by providing precise control decisions to …
advanced autonomous driving systems (ADSs) by providing precise control decisions to …
Evaluating adversarial attacks on driving safety in vision-based autonomous vehicles
In recent years, many deep learning models have been adopted in autonomous driving. At
the same time, these models introduce new vulnerabilities that may compromise the safety …
the same time, these models introduce new vulnerabilities that may compromise the safety …
Multi-source adversarial sample attack on autonomous vehicles
Deep learning has an impressive performance of object detection and classification for
autonomous vehicles. Nevertheless, the essential vulnerability of deep learning models to …
autonomous vehicles. Nevertheless, the essential vulnerability of deep learning models to …
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 …
Securing connected & autonomous vehicles: Challenges posed by adversarial machine learning and the way forward
Connected and autonomous vehicles (CAVs) will form the backbone of future next-
generation intelligent transportation systems (ITS) providing travel comfort, road safety …
generation intelligent transportation systems (ITS) providing travel comfort, road safety …
Adversarial attacks and defenses for deep-learning-based unmanned aerial vehicles
J Tian, B Wang, R Guo, Z Wang… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
The introduction of deep learning (DL) technology can improve the performance of cyber–
physical systems (CPSs) in many ways. However, this also brings new security issues. To …
physical systems (CPSs) in many ways. However, this also brings new security issues. To …
Slowtrack: Increasing the latency of camera-based perception in autonomous driving using adversarial examples
In Autonomous Driving (AD), real-time perception is a critical component responsible for
detecting surrounding objects to ensure safe driving. While researchers have extensively …
detecting surrounding objects to ensure safe driving. While researchers have extensively …