CyLab’s Giulia Fanti, Corina Pasareanu, and Vyas Sekar have been awarded research funding from the C3.ai Digital Transformation Institute (C3.ai DTI), an artificial intelligence (AI) software provider. As part of its third round of awarded research funding, C3.ai DTI is focusing its efforts on using AI to harden information security and strengthen the security of critical infrastructure.
“Cybersecurity is an immediate existential issue,” said Thomas M. Siebel, chairman and CEO of C3 AI, in a company press release. “We are equipping top scientists with the means to advance technology to help secure critical infrastructure.”
Fanti, a professor of electrical and computer engineering, is leading a project titled, “GAN-Aided Automatic Test Case Generation,” which seeks to use machine learning techniques to automatically test software for vulnerabilities. While this topic is well-studied, their project is using recent advances in generative modeling to generate tests with better coverage over the software, meaning they are able to efficiently test a much larger set of potential vulnerabilities.
Sekar, a professor of electrical and computer engineering, is leading a project titled, “Democratizing AI-Driven Security Workflows for Critical Energy Infrastructure,” which seeks to radically improve security operations for critical infrastructures by using AI-driven techniques to automate security-relevant workflows and provide early response to novel threats. Sekar says that unlike cloud-scale hypergiants today, critical infrastructures have fewer resources (monetary and personnel) to tackle cyberthreats, so such AI-driven automation will be even more important to tackle next generation threats.
We are equipping top scientists with the means to advance technology to help secure critical infrastructure.Thomas M. Siebel, chairman and CEO, C3 AI
According to their website, C3.ai DTI selects research proposals that inspire cooperative research and advance machine learning and other AI subdisciplines. Projects are peer-reviewed on scientific merit, prior accomplishments of the principal investigator and co-principal investigators, the use of AI, machine learning, data analytics, and cloud computing in the research project, and the suitability for testing the methods at scale.