AR-GAN: Generative Adversarial Network-Based Defense Method Against Adversarial Attacks on the Traffic Sign Classification System of Autonomous Vehicles. (arXiv:2401.14232v1 [cs.CV])

This study developed a generative adversarial network (GAN)-based defense
method for traffic sign classification in an autonomous vehicle (AV), referred
to as the attack-resilient GAN (AR-GAN). The novelty of the AR-GAN lies in (i)
assuming zero knowledge of adversarial attack models and samples and (ii)
providing consistently high traffic sign classification performance under
various adversarial attack types. The AR-GAN classification system consists of
a generator that denoises an image by reconstruction, and a classifier that
classifies the reconstructed image. The …

adversarial adversarial attack adversarial attacks arxiv attack attacks autonomous autonomous vehicle autonomous vehicles classification defense gan generative knowledge lies network resilient sign study system traffic vehicle vehicles zero knowledge