Key idea: “Adversarial AI is real. The tactics that we used to build models to detect threat vectors are the same tactics adversaries can use to beat our very models that we build.”
Original author and publication date: George Seffers – April 26, 2022
Futurizonte Editor’s Note: Nice job, geniuses! The same AI we developed to help us can now easily turn against us.
From the article:
A panel of artificial intelligence (AI) experts from industry discussed some of the technology’s promise and perils and predicted its future during an AFCEA TechNet Cyber Conference panel April 26 in Baltimore.
The panelists were all members of AFCEA’s Emerging Leaders Committee who have achieved expertise in their given fields before the age of 40. The group discussed AI in the cyber realm.
Asked about “anti-AI” or “counter-AI,” Brian Behe, lead data scientist, CyberPoint International, reported a recent case in which his team used a method called reinforcement learning to change the signature of malware files without altering the malware’s functionality. “We use this as a way to do some security testing on other machine learning classifiers that had been built to detect malware. Sure enough, we were able to beat those classifiers,” Behe explained.
But the same techniques can be used for ulterior purposes. “Additionally, we were able to use those techniques to beat commercial AV [antivirus software] in a number of instances. So, adversarial AI is real. The tactics that we used to build models to detect threat vectors are the same tactics adversaries can use to beat our very models that we build,” he warned.
Behe stressed the importance of curating data sets.
“I would highly encourage, if you think there’s an adversarial component to the problem you’re tackling—a la malware detection—it would be important to look into and research how we can use those techniques, modify malware examples and then introduce that into a training set to hopefully build a better detector,” he said.
The emerging leaders predicted a mixed future for AI technology. For example, Shammara Clarkson, senior software support specialist, IntelliGenesis, sees interest in AI rising and dropping in cycles. “It would be cool if AI could stay relevant. I feel like it’s kind of a cyclical thing. Kind of both in and out of fashion, and I would just hope we can find small solutions that would lead us to that greater good that we’re looking for when it comes to artificial intelligence,” Clarkson said.