Security and Privacy of Machine Learning

Security and privacy in Machine Learning (ML) refer to the measures and practices implemented to protect ML systems, data, and users from unauthorized access, misuse, or breaches of confidentiality. Security in ML involves safeguarding the algorithms, models, and training data from tampering, theft, or adversarial attacks, ensuring the integrity and authenticity of the ML processes. … Read more