Deep-Fake CAPTCHA: Mitigating Next-Generation Social Engineering Attacks
Researchers propose DF-CAPTCHA, a challenge-response defense that verifies callers in voice and video to defeat real-time deepfake impersonation in social engineering.
The DF-CAPTCHA framework prompts call participants with simple challenge-response tasks that are easy for humans but hard for real-time deepfake systems to convincingly generate. Responses are verified on four criteria: realism, identity consistency, task completion, and response time. User studies and experiments with real-time deepfake models across audio and video modalities show substantially improved detection over passive artifact-based methods.
- Active challenge-response outperforms passive deepfake artifact detection
- Verifies realism, identity consistency, task completion, and response time
- Evaluated in both audio and video against real-time deepfake models
- User studies show humans often cannot distinguish real-time deepfake calls
From the original article
1 min read at arxiv.orgThis paper presents DF-CAPTCHA, an active defense against real-time deepfake impersonation in voice and video calls. Instead of passively searching for artifacts, DF-CAPTCHA prompts the caller to perform simple challenge-response tasks that are easy for humans but difficult for current real-time deepfake systems to generate convincingly.
By Guy Frankovits · arxiv.org
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