Hyeong-Gyeong Kim1, Sang-Min Choi2, Hyeon Seo2, Suwon Lee2,*
CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4381-4397, 2025, DOI:10.32604/cmc.2025.067024
- 30 July 2025
Abstract Adversarial attacks pose a significant threat to artificial intelligence systems by exposing them to vulnerabilities in deep learning models. Existing defense mechanisms often suffer drawbacks, such as the need for model retraining, significant inference time overhead, and limited effectiveness against specific attack types. Achieving perfect defense against adversarial attacks remains elusive, emphasizing the importance of mitigation strategies. In this study, we propose a defense mechanism that applies random cropping and Gaussian filtering to input images to mitigate the impact of adversarial attacks. First, the image was randomly cropped to vary its dimensions and then placed… More >
Login
Register
