A comprehensive analysis of adversarial attacks against spam filters

This research paper analyzes adversarial attacks, which are methods where attackers deliberately craft malicious inputs to fool AI systems, specifically targeting spam filters (software that identifies unwanted emails). The study examines how these attacks work and their implications for email security systems that rely on machine learning (AI trained on examples to recognize patterns).