Bringing order to approximate matchng: Classification and attacks on similarity digest algorithms

Details

Serval ID
serval:BIB_B86FF0EC3997
Type
Article: article from journal or magazin.
Collection
Publications
Title
Bringing order to approximate matchng: Classification and attacks on similarity digest algorithms
Journal
Forensic Science International: Digital Investigation
Author(s)
Martín-Pérez Miguel, Rodríguez Ricardo J., Breitinger Frank
ISSN
2666-2817
Publication state
Published
Issued date
04/2021
Volume
36
Pages
301120
Language
english
Abstract
Fuzzy hashing or similarity hashing (a.k.a. bytewise approximate matching) converts digital artifacts into an intermediate representation to allow an efficient (fast) identification of similar objects, e.g., for blacklisting. They gained a lot of popularity over the past decade with new algorithms being developed and released to the digital forensics community. When releasing algorithms (e.g., as part of a scientific article), they are frequently compared with other algorithms to outline the benefits and sometimes also the weaknesses of the proposed approach. However, given the wide variety of algorithms and approaches, it is impossible to provide direct comparisons with all existing algorithms. In this paper, we present the first classification of approximate matching algorithms which allows an easier description and comparisons. Therefore, we first reviewed existing literature to understand the techniques various algorithms use and to familiarize ourselves with the common terminology. Our findings allowed us to develop a categorization relying heavily on the terminology proposed by NIST SP 800-168. In addition to the categorization, this article presents an abstract set of attacks against algorithms and why they are feasible. Lastly, we detail the characteristics needed to build robust algorithms to prevent attacks. We believe that this article helps newcomers, practitioners, and experts alike to better compare algorithms, understand their potential, as well as characteristics and implications they may have on forensic investigations.
Keywords
Approximate matching, Fuzzy hashing, Similarity hashing, Similarity digest algorithm, Bytewise, Classification scheme
Web of science
Open Access
Yes
Create date
06/05/2021 11:01
Last modification date
06/05/2021 11:42
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