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AI security challengesTechNewsWorld
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70% Informative
Machine learning security operations ( MLSecOps ) has emerged to provide a foundation for robust AI security.
As organizations increasingly embed AI and machine learning ( ML ) into their operations, the stakes for securing these systems have never been higher.
MLSecOps emphasizes thorough vetting and continuous monitoring of the AI software supply chain.
AdvML emphasizes the need for continuous monitoring and evaluation of AI systems throughout their lifecycle.
Developers should implement regular assessments, including adversarial training and stress testing, to identify potential weaknesses in their models.
By prioritizing AdvML practices, ML practitioners can proactively safeguard their technologies and reduce the risk of operational failures.
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