Anti-Tamper Protection for Unauthorized Individual Image Generation

TL;DR

This paper introduces Anti-Tamper Perturbation (ATP), a novel method embedding protection and authorization mechanisms in images to defend against forgery and purification attacks, thereby safeguarding portrait rights and privacy.

Contribution

The paper proposes ATP, a new anti-tamper approach combining protection and authorization perturbations in the frequency domain, resilient to purification attacks.

Findings

ATP effectively defends against forgery attacks in various scenarios.

The method preserves authorization sensitivity while disrupting forgery.

Extensive experiments validate robustness of ATP against tampering.

Abstract

With the advancement of personalized image generation technologies, concerns about forgery attacks that infringe on portrait rights and privacy are growing. To address these concerns, protection perturbation algorithms have been developed to disrupt forgery generation. However, the protection algorithms would become ineffective when forgery attackers apply purification techniques to bypass the protection. To address this issue, we present a novel approach, Anti-Tamper Perturbation (ATP). ATP introduces a tamper-proof mechanism within the perturbation. It consists of protection and authorization perturbations, where the protection perturbation defends against forgery attacks, while the authorization perturbation detects purification-based tampering. Both protection and authorization perturbations are applied in the frequency domain under the guidance of a mask, ensuring that the protection perturbation does not disrupt the authorization perturbation. This design also enables the authorization perturbation to be distributed across all image pixels, preserving its sensitivity to purification-based tampering. ATP demonstrates its effectiveness in defending forgery attacks across various attack settings through extensive experiments, providing a robust solution for protecting individuals' portrait rights and privacy. Our code is available at: https://github.com/Seeyn/Anti-Tamper-Perturbation .