Research Article
Similarity Preserving Hashing: Eligible Properties and a New Algorithm
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@INPROCEEDINGS{10.1007/978-3-642-39891-9_11, author={Frank Breitinger and Harald Baier}, title={Similarity Preserving Hashing: Eligible Properties and a New Algorithm }, proceedings={Digital Forensics and Cyber Crime. 4th International Conference, ICDF2C 2012, Lafayette, IN, USA, October 25-26, 2012, Revised Selected Papers}, proceedings_a={ICDF2C}, year={2013}, month={10}, keywords={Digital forensics Similarity Preserving Hashing fuzzy hashing properties of Similarity Preserving Hashing}, doi={10.1007/978-3-642-39891-9_11} }- Frank Breitinger
Harald Baier
Year: 2013
Similarity Preserving Hashing: Eligible Properties and a New Algorithm
ICDF2C
Springer
DOI: 10.1007/978-3-642-39891-9_11
Abstract
Hash functions are a widespread class of functions in computer science and used in several applications, e.g. in computer forensics to identify known files. One basic property of cryptographic Hash Functions is the avalanche effect that causes a significantly different output if an input is changed slightly. As some applications also need to identify similar files (e.g. spam/virus detection) this raised the need for . In recent years, several approaches came up, all with different namings, properties, strengths and weaknesses which is due to a missing definition.
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