Anti-Forensics of Camera Identification and the Triangle Test by Improved Fingerprint-Copy Attack

TL;DR

This paper introduces an improved fingerprint-copy attack that disperses the fingerprint superimposition to evade camera identification and triangle test detection, demonstrating high effectiveness on multiple camera images.

Contribution

The paper presents a novel block-wise, randomized fingerprint-copy attack method that reduces detectability by the triangle test, enhancing attack effectiveness.

Findings

Effectively fools camera identification on 2,900 images from 4 cameras.

Significantly degrades the performance of the triangle test.

Reduces the impact of non-PRNU components in forged images.

Abstract

The fingerprint-copy attack aims to confuse camera identification based on sensor pattern noise. However, the triangle test shows that the forged images undergone fingerprint-copy attack would share a non-PRNU (Photo-response nonuniformity) component with every stolen image, and thus can detect fingerprint-copy attack. In this paper, we propose an improved fingerprint-copy attack scheme. Our main idea is to superimpose the estimated fingerprint into the target image dispersedly, via employing a block-wise method and using the stolen images randomly and partly. We also develop a practical method to determine the strength of the superimposed fingerprint based on objective image quality. In such a way, the impact of non-PRNU component on the triangle test is reduced, and our improved fingerprint-copy attack is difficultly detected. The experiments evaluated on 2,900 images from 4 cameras show that our scheme can effectively fool camera identification, and significantly degrade the performance of the triangle test simultaneously.