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 ...
The Artificial Intelligence and Machine Learning (“AI/ML”) risk environment is in flux. One reason is that regulators are shifting from AI safety to AI innovation approaches, as a recent DataPhiles ...
Machine learning (ML) and artificial intelligence (AI) are essential components in modern and effective cybersecurity solutions. However, as the use of ML and AI in cybersecurity is increasingly ...
We are witnessing a rapid advancement of AI and its impact across various industries. However, with great power comes great responsibility, and one of the emerging challenges in the AI landscape is ...
RIT computer science professor Weijie Zhao has earned a National Science Foundation CAREER Award to defend machine learning ...
The final guidance for defending against adversarial machine learning offers specific solutions for different attacks, but warns current mitigation is still developing. NIST Cyber Defense The final ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Microsoft, the nonprofit MITRE Corporation, and 11 organizations ...
Pawelczyk, Martin, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, and Himabindu Lakkaraju. "Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and ...
Researchers from machine learning lab OpenAI have discovered that their state-of-the-art computer vision system can be deceived by tools no more sophisticated than a pen and a pad. As illustrated in ...
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