NIST Creates Cybersecurity Playbook for Generative AI
The US National Institute of Standards and Technology (NIST) has published a report laying out in detail the types of cyberattacks that could be aimed at AI systems as well as possible defenses against them.
The agency believes such a report is critical because current defenses against cyberattacks on AI systems are lackluster – at a time when AI is increasingly pervading all aspects of life and business.
Called “Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations,” the report starts by developing a taxonomy and terminology of adversarial ML, which in turn will help secure AI systems as developers have a uniform basis from which to form defenses. The report covers two broad types of AI: predictive AI and generative AI. These systems are trained on vast amounts of data, which bad actors may act to corrupt. This is not inconceivable since these datasets are too large for people to monitor and filter.
