{"id":7210,"date":"2025-02-04T17:15:37","date_gmt":"2025-02-04T23:15:37","guid":{"rendered":"https:\/\/www.darkreading.com\/vulnerabilities-threats\/how-are-modern-fraud-groups-using-gen-ai-and-deepfakes"},"modified":"2025-02-04T17:15:37","modified_gmt":"2025-02-04T23:15:37","slug":"how-are-modern-fraud-groups-using-genai-and-deepfakes","status":"publish","type":"post","link":"https:\/\/ddi.mohflo.net\/index.php\/2025\/02\/04\/how-are-modern-fraud-groups-using-genai-and-deepfakes\/","title":{"rendered":"How Are Modern Fraud Groups Using GenAI and Deepfakes?"},"content":{"rendered":"
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QUESTION: How are modern fraud groups using generative AI and deepfakes to steal millions of dollars?<\/span><\/span><\/p>\n

If you imagine a fake identity document, what springs to mind? Is it a faded World War II-era identity card with a false name written in neat script next to a black and white photo? Is it a driver\u2019s license from a state you had never actually been to with your photo and a fake name, address and birthday that you showed to the bars in your college town so that you could drink underage? Sometimes those documents worked. Sometimes they didn\u2019t.<\/span><\/p>\n

The forgeries created by modern fraud groups utilize cutting-edge artificial intelligence-driven deepfake technology to create fake identities, avatars and documents that even a trained eye would have trouble spotting, says <\/span>Ofer Freidman, chief business development officer of identity verification and ID management automation company AU10TIX. <\/span><\/span>These groups are using generative AI to steal personal data, craft convincing fake identities, and execute fraud schemes.<\/span><\/p>\n

Fraudsters acquire personal data from individuals through a combination of methods including phishing and social engineering, and hacking corporate databases.They can also just buy the information from cybercrime marketplaces. They can then use an AI system to randomize the information such as names, addresses and document numbers to generate new fake identities. AI is better at avoiding repetitive patterns than humans, making it more likely that these fake identities will evade detection systems and monitors, Friedman says. <\/span><\/p>\n

Traditional forgeries could be identified by spotting inconsistencies, such as mismatched shadows or areas that were low resolution compared to the rest. While there are ways to identify deepfakes (like counting the fingers on the peron’s hands), each model is getting better at producing uniform, high-quality content. <\/span><\/p>\n

For fraudsters, every payday doesn’t need to be huge because they are operating in an “industrialized, systematic way,” Friedman says. “You can go for a million dollars or you can go 100 times for $10,000. It’s the same effort because it’s a machine doing it for you, unlike the good old days when you actually had to do it one by one.\u201d <\/span><\/p>\n

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