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ForBild: Efficient Robust Image Hashing

Steinebach, Martin ; Liu, Huajian ; Yannikos, York (2012)
ForBild: Efficient Robust Image Hashing.
Conference or Workshop Item, Bibliographie

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.

Item Type: Conference or Workshop Item
Erschienen: 2012
Creators: Steinebach, Martin ; Liu, Huajian ; Yannikos, York
Type of entry: Bibliographie
Title: ForBild: Efficient Robust Image Hashing
Language: German
Date: 2012
Book Title: Proceeding of Electronic Imaging - Media Watermarking, Security, and Forensics 2012, January 2012
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.

Uncontrolled Keywords: Secure Data
Identification Number: TUD-CS-2012-0150
Divisions: LOEWE > LOEWE-Zentren > CASED – Center for Advanced Security Research Darmstadt
LOEWE > LOEWE-Zentren
LOEWE
Date Deposited: 30 Dec 2016 20:23
Last Modified: 17 May 2018 13:02
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