Efficiently Mitigating Face-Swap-Attacks: Compressed-PRNU Verification with Sub-Zones

نویسندگان

چکیده

Face-swap-attacks (FSAs) are a new threat to face recognition systems. FSAs essentially imperceptible replay-attacks using an injection device and generative networks. By placing the between camera computer device, attackers can present any as desired. This is particularly potent it also maintains liveliness features, sophisticated alternation of real person, go undetected by traditional anti-spoofing methods. To address FSAs, this research proposes noise-verification framework. Even best networks today leave alteration traces in photo-response noise profile; these detected doing comparison challenge images against enrollment. introduces compression sub-zone analysis for efficiency. Benchmarking with open-source tampering-detection algorithms shows proposed compressed-PRNU verification robustly verifies facial-image authenticity while being significantly faster. demonstrates novel efficiency mitigating face-swap-attacks, including denial-of-service attacks.

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ژورنال

عنوان ژورنال: Technologies (Basel)

سال: 2022

ISSN: ['2227-7080']

DOI: https://doi.org/10.3390/technologies10020046