Deepfake technology is rapidly advancing, posing significant challenges to the detection of manipulated media content. Parallel to that, some adversarial attack techniques have been developed to fool the deepfake detectors and make deepfakes even more difficult to be detected. This paper explores the application of super resolution techniques as a possible adversarial attack in deepfake detection. Through our experiments, we demonstrate that minimal changes made by these methods in the visual appearance of images can have a profound impact on the performance of deepfake detection systems. We propose a novel attack using super resolution as a quick, black-box and effective method to camouflage fake images and/or generate false alarms on pristine images. Our results indicate that the usage of super resolution can significantly impair the accuracy of deepfake detectors, thereby highlighting the vulnerability of such systems to adversarial attacks. The code to reproduce our experiments is available at: https://github.com/davide-coccomini/Adversarial-Magnification-to-Deceive-Deepfake-Detection-through-Super-Resolution

通过实验，我们展示了超分辨率技术在深度伪造检测中的应用作为一种潜在的对抗攻击方法，通过对图像视觉外观的微小改变能对深度伪造检测系统的性能产生深远的影响。我们提出了一种新颖的攻击方法，使用超分辨率作为一种快速、黑盒和有效的方法，来伪装假图像和/或在原始图像上生成虚假的警报。我们的结果表明，超分辨率的使用可以显著损害深度伪造检测器的准确性，从而突显这种系统对对抗性攻击的脆弱性。我们的实验代码可在此链接中获取：this https URL

对抗性放大技术通过超分辨率欺骗深度伪造检测