Can I read Robustness of Practical Perceptual Hashing Algorithms to Hash-Evasion and Hash-Inversion Attacks on EtoBox?

Robustness of Practical Perceptual Hashing Algorithms to Hash-Evasion and Hash-Inversion Attacks by Madden, Jordan; Bhavsar, Moxanki; Dorje, Lhamo; Li, Xiaohua is a scholarly article available to read on EtoBox.

What is Robustness of Practical Perceptual Hashing Algorithms to Hash-Evasion and Hash-Inversion Attacks about?

Perceptual hashing algorithms (PHAs) are widely used for identifying illegal online content and are thus integral to various sensitive applications. However, due to their hasty deployment in real-world scenarios, their adversarial security has not been thoroughly evaluated. This paper assesses the security of three widely utilized PHAs - PhotoDNA, PDQ, and NeuralHash - against hash-evasion and hash-inversion attacks. Contrary to existing literature, our findings indicate that these PHAs demonstrate significant robustness against such attacks. We provide an explanation for these differing results, highlighting that the inherent robustness is partially due to the random hash variations characteristic of PHAs. Additionally, we propose a defense method that enhances security by intentionally introducing perturbations into the hashes.

Author

Madden, Jordan; Bhavsar, Moxanki; Dorje, Lhamo; Li, Xiaohua

Published

2024

Language

EN