A New Edit Distance for Fuzzy Hashing Applications
| Autor: | Gayoso Martínez, Víctor, Hernández Álvarez, Fernando, Hernández Encinas, Luis, Sánchez Ávila, Carmen |
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| Přispěvatelé: | Comunidad de Madrid, Ministerio de Economía y Competitividad (España) |
| Rok vydání: | 2015 |
| Předmět: | |
| Zdroj: | Digital.CSIC. Repositorio Institucional del CSIC instname |
| Popis: | 7 páginas, 5 tablas, 2 algoritmos. Comunicación presentada en: The 2015 World Congress in Computer Science, Computer Engineering, and Applied Computing (WORLDCOMP'15). The 2015 International Conference on Security and Management (SAM'15), Las Vegas, USA, July 27 - 30 Similarity preserving hashing applications, also known as fuzzy hashing functions, help to analyse the content of digital devices by performing a resemblance comparison between different files. In practice, the similarity matching procedure is a two-step process, where first a signature associated to the files under comparison is generated, and then a comparison of the signatures themselves is performed. Even though ssdeep is the best-known application in this field, the edit distance algorithm that ssdeep uses for performing the signature comparison is not well-suited for certain scenarios. In this contribution we present a new edit distance algorithm that better reflects the similarity of two strings, and that can be used by fuzzy hashing applications in order to improve their results. This work has been partially supported by Comunidad de Madrid (Spain) under the project S2013/ICE-3095-CM (CIBERDINE) and by Ministerio de Economía y Com- petitividad (Spain) under the grant TIN2014-55325-C2-1-R (ProCriCiS). |
| Databáze: | OpenAIRE |
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