Research Article
Robust Hashing for Efficient Forensic Analysis of Image Sets
@INPROCEEDINGS{10.1007/978-3-642-35515-8_15, author={Martin Steinebach}, title={Robust Hashing for Efficient Forensic Analysis of Image Sets}, proceedings={Digital Forensics and Cyber Crime. Third International ICST Conference, ICDF2C 2011, Dublin, Ireland, October 26-28, 2011, Revised Selected Papers}, proceedings_a={ICDF2C}, year={2012}, month={12}, keywords={}, doi={10.1007/978-3-642-35515-8_15} }- Martin Steinebach
Year: 2012
Robust Hashing for Efficient Forensic Analysis of Image Sets
ICDF2C
Springer
DOI: 10.1007/978-3-642-35515-8_15
Abstract
Forensic analysis of image sets today is most often done with the help of cryptographic hashes due to their efficiency, their integration in forensic tools and their excellent reliability in the domain of false detection alarms. A drawback of these hash methods is their fragility to any image processing operation. Even a simple re-compression with JPEG results in an image not detectable. A different approach is to apply image identification methods, allowing identifying illegal images by e.g. semantic models or facing detection algorithms. Their common drawback is a high computational complexity and significant false alarm rates. Robust hashing is a well-known approach sharing characteristics of both cryptographic hashes and image identification methods. It is fast, robust to common image processing and features low false alarm rates. To verify its usability in forensic evaluation, in this work we discuss and evaluate the behavior of an optimized block-based hash.
