Machine Learning Security focuses on protecting machine learning models from adversarial attacks that can compromise their integrity, confidentiality, and availability. It encompasses a range of strategies to detect, prevent, and mitigate threats that exploit vulnerabilities in the data, algorithms, and deployment environments of these systems.