Research Article
Expediting Approximate Matching with Hierarchical Bloom Filter Trees
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@INPROCEEDINGS{10.1007/978-3-319-73697-6_11, author={David Lillis and Frank Breitinger and Mark Scanlon}, title={Expediting Approximate Matching with Hierarchical Bloom Filter Trees}, proceedings={Digital Forensics and Cyber Crime. 9th International Conference, ICDF2C 2017, Prague, Czech Republic, October 9-11, 2017, Proceedings}, proceedings_a={ICDF2C}, year={2018}, month={1}, keywords={Approximate matching Hierarchical bloom filter trees }, doi={10.1007/978-3-319-73697-6_11} }- David Lillis
Frank Breitinger
Mark Scanlon
Year: 2018
Expediting Approximate Matching with Hierarchical Bloom Filter Trees
ICDF2C
Springer
DOI: 10.1007/978-3-319-73697-6_11
Abstract
Perhaps the most common task encountered by digital forensic investigators consists of searching through a seized device for pertinent data. Frequently, an investigator will be in possession of a collection of “known-illegal” files (e.g. a collection of child pornographic images) and will seek to find whether copies of these are stored on the seized drive. Traditional hash matching techniques can efficiently find files that precisely match. However, these will fail in the case of merged files, embedded files, partial files, or if a file has been changed in any way.
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