… of five adversarial attacks and four defense methods on three driving models. Experiments
… Therefore, adversarial attacks on driving models are defined with respect to an acceptable …

… investigation of adversarial attacks on the automated driving ecosystem. In addition, a survey
of adversarial defense models for improving resistance against adversarial attacks on ML …

… In Section III, we briefly introduce the attack model of the two adversarial attacks studied in
this article. In Section IV, we elaborate on our proposed end-to-end evaluation framework and …

… The model parameters are trained via adversarial training with the … adversarial training
methods in state-of-the-art stereo-based 3D object detection models for autonomous vehicles. …

… autonomous driving models against adversarial attacks and … our approach using four
adversarial attacks in both Whitebox … the normal behavior of the model into memory vectors. By …

… review the progress of adversarial attacks on different deep learning models in ADSs. … for
current autonomous vehicles to defend against adversarial attacks as the majority of existing …

… systems, they are found vulnerable to adversarial attacks where small-magnitude …
adversarial roadside sign Sadv to have adversarial effect on the target autonomous driving model …

… adversarial attacks against an end-to-end regression model for autonomous driving: one
strong attack … ), and one stealth attack that produces a universal adversarial perturbation that …

… Moreover, attacks typically involve carefully constructed adversarial examples at the level of
… -end attacks on autonomous driving in simulation, using simple physically realizable attacks: …

… the robustness of a model for autonomous driving requires: 1) … tested models and 2)
considering real-world adversarial exam… attack pipeline used to generate real-time adversarial …