Efficient and reliable automated detection of modified image and multimedia files has long been a challenge for law enforcement, compounded by the harm caused by repeated exposure to psychologically harmful materials. In August 2019 Facebook open-sourced their PDQ and TMK + PDQF algorithms for image and video similarity measurement, respectively. In this report, we review the algorithms' performance on detecting commonly encountered transformations on real-world case data, sourced from contemporary investigations. We also provide a reference implementation to demonstrate the potential application and integration of such algorithms within existing law enforcement systems.
@article{arxiv.1912.07745,
title = {PDQ & TMK + PDQF -- A Test Drive of Facebook's Perceptual Hashing Algorithms},
author = {Janis Dalins and Campbell Wilson and Douglas Boudry},
journal= {arXiv preprint arXiv:1912.07745},
year = {2019}
}
Comments
Submitted to Journal of Digital Investigation 08 SEP 2019. Under review as at 13 December 2019