NIST: There Is No Perfect Solution to Prevent Adversarial Machine Learning Attacks

machine learning attacks

In a report on adversarial machine learning attacks and mitigations, NIST issued a warning, stating that there is no foolproof solution to deal with these kinds of threats.

The process of extracting details about the traits and actions of a machine learning system and modifying inputs to achieve a desired result is known as adversarial machine learning, or AML.

NIST has released guidelines outlining the different kinds of attacks that can be used against AI systems, alerting users and developers to the fact that there isn’t yet a perfect way to safeguard these systems. The agency has urged the community to try to come up with stronger defenses.

Read More: NIST: No Silver Bullet Against Adversarial Machine Learning Attacks

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