An Improved Statistic for the Pooled Triangle Test against PRNU-Copy Attack

TL;DR

This paper introduces an improved statistic for the pooled triangle test that better detects PRNU-copy attacks by leveraging the one-tail nature of deviations, showing enhanced performance in challenging scenarios.

Contribution

The paper presents a novel statistic that exploits the one-tail property of the test, improving detection accuracy against fingerprint-copy attacks.

Findings

Superior performance in challenging attack scenarios

Effective with large number of attack images

Better detection with small test images

Abstract

We propose a new statistic to improve the pooled version of the triangle test used to combat the fingerprint-copy counter-forensic attack against PRNU-based camera identification [1]. As opposed to the original version of the test, the new statistic exploits the one-tail nature of the test, weighting differently positive and negative deviations from the expected value of the correlation between the image under analysis and the candidate images, i.e., those image suspected to have been used during the attack. The experimental results confirm the superior performance of the new test, especially when the conditions of the test are challenging ones, that is when the number of images used for the fingerprint-copy attack is large and the size of the image under test is small.