Securing Machine Learning Algorithms

Based on a systematic review of relevant literature on machine learning, in this report we provide a taxonomy for machine learning algorithms, highlighting core functionalities and critical stages. The report also presents a detailed analysis of threats targeting machine learning systems. Identified threats include inter alia, data poisoning, adversarial attacks and data exfiltration. Finally, we propose concrete and actionable security controls described in relevant literature and security frameworks and standards.

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