Adversarial attacks in machine learning: What they are and how to stop them - JackOfAllTechs.com

Adversarial machine learning, a technique that attempts to fool models with deceptive data, is a growing threat in the AI and machine learning research community. The most common reason is to cause a malfunction in a machine learning model. An adversarial attack might entail presenting a model with inaccurate or misrepresentative data as it's training, or introducing maliciously designed data to deceive an already trained model. As the U.S. National Security Commission on Artificial Intelligence's 2019 interim report notes, a very small percentage of current AI research goes toward defending AI systems against adversarial efforts. Some systems already used in production could be vulnerable to attack.