arXiv Artificial Intelligence

Deep-Fake CAPTCHA: Mitigating Next-Generation Social Engineering Attacks

Deep-Fake CAPTCHA: Mitigating Next-Generation Social Engineering Attacks

Quick summary

arXiv:2609.11404v1 Announce Type: cross Abstract: This 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. The framework verifies the response using four criteria: realism, identity consistency, task completion, and response time. We evaluate the approach across both audio and video modalities using user studies and

Key takeaways

  • arXiv:2609.11404v1 Announce Type: cross Abstract: This 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.
  • The framework verifies the response using four criteria: realism, identity consistency, task completion, and response time.

Why it matters

“Deep-Fake CAPTCHA: Mitigating Next-Generation Social Engineering Attacks” shows why AI risk cannot be reduced to answer accuracy. Access controls, logging, human approval and incident response need to be designed into the workflow from the start.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗