ML Security Principles
By John Paul Mueller, Rod Stephens
Packt Publishing
300 pages
Published: 2022-12-30
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Publisher Description
As AI integrates into critical infrastructure, the vulnerability of machine learning models presents a new frontier for cyber threats. This technical guide equips security professionals with the methodologies required to defend ML pipelines against adversarial attacks like data poisoning, deepfakes, and model evasion, ensuring the resilience of intelligent systems.
Match Rate:
9.5/10
(Relevance to core cybersecurity goals)