As CISOs work to future proof their cybersecurity strategy and infrastructure for tomorrow’s emerging threats, artificial intelligence (AI) attacks are looming large in their thoughts. Even without the hype that’s billowed around ChatGPT and generative AI’s skyrocketing popularity, AI risk has started to unfold as a growing concern among security researchers and pundits in 2023. Security advocates are warning CISOs that they’re fighting a two-front war when it comes to AI risk and resilience. Not only do they need to be wary of the threat posed by adversarial AI attacks against enterprise deployments of AI and machine learning (ML) models, but they must also defend themselves from a greater volume of attacks fueled by the bad guys’ use of AI in their offensive campaigns. One of the attack types that should concern CISOs from a data and process integrity standpoint are poisoning attacks. The principle behind these attacks is that by manipulating the data which a deep learning model trains upon, an attacker can either corrupt the model (untargeted) or even manipulate its output to produce favorable results for the attacker (targeted).
Full slideshow : 10 Types of AI Attacks CISOs Should Track.
