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.
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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Steinebach, M. (2012). Robust Hashing for Efficient Forensic Analysis of Image Sets. In: Gladyshev, P., Rogers, M.K. (eds) Digital Forensics and Cyber Crime. ICDF2C 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 88. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35515-8_15
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DOI: https://doi.org/10.1007/978-3-642-35515-8_15
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