Deepfakes are a powerful tool for malicious actors, and digital injection attacks exploit a vulnerability in how we verify identities online.
Deepfakes use AI, particularly deep learning algorithms, to manipulate existing media. They stitch together video clips, swap faces in real-time or even synthesize entirely new audio recordings. Just picture a realistic video that shows a CEO announcing a fake merger, or an audio recording seemingly spoken by a politician endorsing a rival candidate
The ease with which deepfakes can be created makes them a growing concern, especially for spreading misinformation and tarnishing reputations.
Picture bad actors using these deepfakes to bypass security measures. This is where digital injection attacks come in. Instead of simply showing a fake video publicly, attackers "inject" it directly into the system responsible for verifying your identity. For example, during a video call for bank verification, a deepfake could replace your face with someone else's, which allows unauthorized access. Similarly, a deepfake voice recording might trick a voice recognition system.
The danger lies in the fact that these attacks target the system itself, not your vigilance. Traditional security measures like passwords become useless when the system "sees" a deepfaked version of you.
It’s not all doom and gloom though. The good news is that security experts are aware of this growing threat. Companies are developing detection methods that analyze video and audio for inconsistencies that might reveal manipulation.
One company in particular is AuthenticID, which announced the release of a new solution to detect deep fake and generative AI injection attacks.
Founded in 2001, AuthenticID has expertise in verifying government-issued identification documents with a next-generation, automated AI platform for fraud detection and identity verification. AuthenticID’s patented platform is used by financial services firms, wireless carriers and identity verification platforms.
AuthenticID’s Injection Attack Solution uses three methods with targeted, proprietary algorithms.
- Visual fraud algorithms to detect counterfeit and synthetic elements in content.
- Text fraud algorithms to detect errors within false documents.
- Behavioral algorithms focusing on activity during the capture and submission of an ID.
The AuthenticID identity verification solution is 100% automated, and the solution’s automation means there is no human bias or lag time introduced in the detection and decisioning process. According to the official press release, stopping injection attacks and deep fake attacks can be done in a workflow in a matter of milliseconds.
"The widespread availability of inexpensive, easy-to-use tools allows bad actors to create highly convincing fake identity documents and biometrics,” said Alex Wong, vice president of product management at AuthenticID. “Our deep fake injection attack solution meets a critical need to determine the legitimacy of a user in this new era of technology.”
With that said, the algorithms used by AuthenticID’s Product and Applied Research team for the new solution are not a “silver bullet” in the fight against injection attacks and other identity fraud methods.
Malicious actors always change methods, sometimes daily. They develop new ways to circumvent identify verification and security measures. That is why AuthenticID’s Identity Fraud Taskforce is committed to continuously developing new algorithms and improving the identity verification decisioning engine to ensure new fraud vectors can be identified and stopped.
AuthenticID will continue to drive innovation forward in its technology so companies stay ahead of changing fraud techniques and regulatory requirements.
Edited by
Greg Tavarez
