The Challenge of Detecting 'Deepfakes'Avivah Litan of Gartner on Countering the Next Generation of Socially Engineered Fraud
Detecting “deepfake” images used by fraudsters is challenging, says Gartner Research analyst Avivah Litan. And determined adversaries will keep pace with deepfake detection efforts by using artificial intelligence network learning processes, she says.
Nevertheless, security pros can use a combination of deepfake detection algorithms, internet whitelisting and fraud detection techniques to fight socially engineered attacks fueled by deepfakes, she says.
In a video interview with Information Security Media Group, Litan discusses:
- Current benign and malicious use cases for deepfakes;
- Strategies for increasing deepfake detection rates;
- The use of technology to determine the provenance of news sources.
Litan, vice president and distinguished analyst at Gartner Research, is a member of the firm’s ITL application innovation team that covers blockchain, artificial intelligence and IoT. She specializes in blockchain innovation, securing and protecting AI, trustworthy AI and how to detect fake content and goods using a variety of technologies and methods. She chairs Gartner's blockchain research community of analysts and also helps manage the company’s research for application leaders.