Research Papers on Adversarial Attacks

Research papers on adversarial attacks explore how malicious modifications to input data can deceive AI systems, such as image recognition or language processing. These attacks involve subtle changes that are often imperceptible to humans but cause AI models to make mistakes, like misidentifying objects or words. Studying these vulnerabilities helps researchers develop defenses to make AI systems more robust and secure. Overall, this research aims to understand, detect, and guard against methods that could exploit AI vulnerabilities in real-world applications.