Paste Attack

Paste attacks encompass a range of techniques exploiting the ease of digitally manipulating images and videos by cropping and pasting content to deceive systems or bypass security measures. Current research focuses on developing robust watermarking methods, such as self-synchronizing object-aligned watermarking, to resist these attacks, as well as automated methods for detecting vulnerabilities in deep neural networks susceptible to copy-paste manipulations. These efforts are crucial for safeguarding digital content, enhancing the security of biometric systems (like face recognition), and improving the reliability of AI models by identifying and mitigating their susceptibility to adversarial examples.