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Privacy and Robust Hashes

 
: Steinebach, Martin; Lutz, Sebastian; Liu, Huajian

:

Association for Computing Machinery -ACM-:
ARES 2019, 14th International Conference on Availability, Reliability and Security. Proceedings : Canterbury, CA, United Kingdom, August 26 - 29, 2019
New York: ACM, 2019
ISBN: 978-1-4503-7164-3
Art. 70, 8 S.
International Conference on Availability, Reliability and Security (ARES) <14, 2019, Canterbury>
Englisch
Konferenzbeitrag
Fraunhofer SIT ()

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.

: http://publica.fraunhofer.de/dokumente/N-565415.html