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2019
Conference Paper
Titel

Privacy and Robust Hashes

Abstract
Within a forensic examination of a computer for illegal image content, robust hashing can be used to detect images even after they have been altered. Here the perceptible properties of an image are used to create the hash values. Whether an image has the same content is determined by a distance function. Cryptographic hash functions, on the other hand, create a unique bit-sensitive value. With these, no similarity measurement is possible, since only with exact agreement a picture is found. A minimal change in the image results in a completely different cryptographic hash value. However, the robust hashes have an big disadvantage: hash values can reveal something about the structure of the picture. This results in a data protection leak. The advantage of a cryptographic hash function is in turn that its values do not allow any conclusions about the structure of an image. The aim of this work is to develop a procedure for which combines the advantages of both hashing functions.
Author(s)
Steinebach, Martin
Fraunhofer-Institut für Sichere Informationstechnologie SIT
Lutz, Sebastian
Fraunhofer-Institut für Sichere Informationstechnologie SIT
Liu, Huajian
Fraunhofer-Institut für Sichere Informationstechnologie SIT
Hauptwerk
ARES 2019, 14th International Conference on Availability, Reliability and Security. Proceedings
Konferenz
International Conference on Availability, Reliability and Security (ARES) 2019
Thumbnail Image
DOI
10.1145/3339252.3340105
Language
English
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Fraunhofer-Institut für Sichere Informationstechnologie SIT
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