… Thus, to speed up the process of generating adversarial samples in the autonomous vehicle
scenario, we utilize a generation-based approach that is more efficient than the optimization-…

… This process is carried out by using actor-critic learning based on the NewtonRaphson
method in the sample studied scenario. We additionally show how an intrusion detection system …

… samples, T N O = the number of correctly identified negative samples, F P O = the number
of wrongly identified positive samples, and F N O = the number of wrongly identified negative …

… is to use filtered noise to introduce undesired correlation in the received radar signal
samples, so that we can use multiple attackers to fake the location of existing obstacles. a) …

… In this work, we assume that the attacker who carries out the poisoning attack has the ability
of injecting corrupted samples into the training dataset and the attacker who implements …

… Besides, our survey paper covers the recent developments of attacks and defenses on CAVs,
including three ethical hacking studies on Tesla and Baidu autonomous vehicles in 2019. …

… attack the multiple object detector we replace yfool with a near zero vector and otherwise follow
the recipe for attacking … : from phenomena to blackbox attacks using adversarial samples. …

… by autonomous vehicle manufacturers without unauthorized access. Therefore, the black-box
attack … 2) We develop a learnable sampling strategy in our ASA method by replacing the …

… , various studies [34,35] have successfully shown that DL models such as classification
models, with the introduction of GAN attack can misclassify the legitimate sample. These …

… autonomous vehicle (AV)-based applications is constrained by the DL models’ susceptibility
to adversarial attacks … Cai, “Multi-source adversarial sample attack on autonomous vehicles,…