Can generative AI be an ally in rooting out ransomware threats? A UC researcher suggests rethinking ways to catch bad actors The online publication, Securities.io, reports that ransomware attacks on business activity are projected to exceed $265 billion annually by 2031. Using generative AI to find a way to help alleviate these cybersecurity threats may be a smart option. Securities.io cites recent research published by Nelly Elsayed, associate professor in the UC School of Information Technology, in the Journal of Information Security and Applications, which suggests that generative AI may be an ally in strengthening ransomware defense. “We are in a hype era of AI,” says Elsayed, founder and leader of the Applied Machine Learning and Intelligence Lab within the College of Education, Criminal Justice, and Human Services. “Some people support it, others fear it, but in general people who design technology are trying to use it for good.” Elsayed's research article argues that generative AI can be used to integrate synthetic data generation and behavioral forecasting, stress test systems by checking for adversarial behavior simulation and improve trust of human-AI collaboration in security operation systems. Cybersecurity analysts and system defenders can use AI to detect new malicious attacks and classify and identify new means of attack from bad actors, according to Elsayed. Simulating with hackers might allow for creating possible attack scenarios and learning to think like attackers to offer more robust tools for defense, she adds. “It’s a way to generate a combination of possible attacks system defenders might not have considered,” she says. Elsayed adds a practical example could be a user pasting a suspicious email into a generative AI system and asking about the validity of the email. AI could help screen and catch red flags: a suspicious logo or misspellings. “AI can become an early