An Improved Statistic for the Pooled Triangle Test against PRNU-Copy Attack
This work addresses a specific counter-forensic attack in digital image forensics, offering an incremental improvement to existing detection methods.
The authors tackled the problem of detecting fingerprint-copy attacks in PRNU-based camera identification by proposing a new statistic for the pooled triangle test, which weights positive and negative deviations differently to exploit the one-tail nature of the test, resulting in superior performance, especially under challenging conditions like large attack image numbers and small test image sizes.
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.