A survey of end-to-end driving: Architectures and training methods
A Tampuu, T Matiisen, M Semikin… - … on Neural Networks …, 2020 - ieeexplore.ieee.org
Autonomous driving is of great interest to industry and academia alike. The use of machine
learning approaches for autonomous driving has long been studied, but mostly in the …
learning approaches for autonomous driving has long been studied, but mostly in the …
A systematic survey of attack detection and prevention in connected and autonomous vehicles
T Limbasiya, KZ Teng, S Chattopadhyay… - Vehicular …, 2022 - Elsevier
The number of Connected and Autonomous Vehicles (CAVs) is increasing rapidly in various
smart transportation services and applications, considering many benefits to society, people …
smart transportation services and applications, considering many benefits to society, people …
Invisible for both camera and lidar: Security of multi-sensor fusion based perception in autonomous driving under physical-world attacks
In Autonomous Driving (AD) systems, perception is both security and safety critical. Despite
various prior studies on its security issues, all of them only consider attacks on camera-or …
various prior studies on its security issues, all of them only consider attacks on camera-or …
Physical attack on monocular depth estimation with optimal adversarial patches
Deep learning has substantially boosted the performance of Monocular Depth Estimation
(MDE), a critical component in fully vision-based autonomous driving (AD) systems (eg …
(MDE), a critical component in fully vision-based autonomous driving (AD) systems (eg …
“real attackers don't compute gradients”: bridging the gap between adversarial ml research and practice
Recent years have seen a proliferation of research on adversarial machine learning.
Numerous papers demonstrate powerful algorithmic attacks against a wide variety of …
Numerous papers demonstrate powerful algorithmic attacks against a wide variety of …
You can't see me: Physical removal attacks on {lidar-based} autonomous vehicles driving frameworks
Autonomous Vehicles (AVs) increasingly use LiDAR-based object detection systems to
perceive other vehicles and pedestrians on the road. While existing attacks on LiDAR-based …
perceive other vehicles and pedestrians on the road. While existing attacks on LiDAR-based …
[PDF][PDF] Avoiding an oppressive future of machine learning: A design theory for emancipatory assistants
Widespread use of machine learning (ML) systems could result in an oppressive future of
ubiquitous monitoring and behavior control that, for dialogic purposes, we call “Informania.” …
ubiquitous monitoring and behavior control that, for dialogic purposes, we call “Informania.” …
Attacks on self-driving cars and their countermeasures: A survey
Intelligent Traffic Systems (ITS) are currently evolving in the form of a cooperative ITS or
connected vehicles. Both forms use the data communications between Vehicle-to-Vehicle …
connected vehicles. Both forms use the data communications between Vehicle-to-Vehicle …
Dirty road can attack: Security of deep learning based automated lane centering under {Physical-World} attack
Automated Lane Centering (ALC) systems are convenient and widely deployed today, but
also highly security and safety critical. In this work, we are the first to systematically study the …
also highly security and safety critical. In this work, we are the first to systematically study the …
A survey of attacks on controller area networks and corresponding countermeasures
HJ Jo, W Choi - IEEE Transactions on Intelligent Transportation …, 2021 - ieeexplore.ieee.org
The development of vehicle technologies such as connected and autonomous vehicle
environments provide drivers with functions for convenience and safety that are highly …
environments provide drivers with functions for convenience and safety that are highly …