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

arxiv.org/abs/2609.11404

quality89

Updated 2 h ago · first seen 12 Sept 2026

paper_01M29X34Y017BRWM2VYJM3P876

Published
12 Sept 2026
T1 · 2 h ago
arXiv
2609.11404
T1 · 2 h ago
Category
cs.CR
T1 · 2 h ago

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 experiments with real-time deepfake models. Results show that people often struggle to distinguish real-time deepfakes from authentic media, while DF-CAPTCHA substantially improves detection performance over passive methods, reaching high accuracy in both modalities. These findings suggest that active challenge-based verification is a practical and robust defense against next-generation social engineering attacks based on real-time deepfakes.

Authors 4

Fred M. Grabovski, Guy Frankovits, Lior Yasur, Yisroel Mirsky

Specification

Official page

Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

Arxiv announce type
cross

Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

arXiv id
2609.11404

Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

Categories
cs.AI, cs.CR

Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

PDF

Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

Primary category
cs.CR

Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

Published
12 Sept 2026

Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

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Provenance

Attributed facts

9

Source tiers

T19

Freshest observation

2 h ago

Conflicts

None