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Slice Distance: An Insert-Only Levenshtein Distance with a Focus on Security Applications
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (PRISEC)ORCID-id: 0000-0001-9886-6651
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (DISCO)ORCID-id: 0000-0003-3461-7079
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (PRISEC)ORCID-id: 0000-0003-0778-4736
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (DISCO)ORCID-id: 0000-0001-7311-9334
2018 (engelsk)Inngår i: Proceedings of NTMS 2018 Conference and Workshop, New York: IEEE, 2018, s. 1-5Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Levenshtein distance is well known for its use in comparing two strings for similarity. However, the set of considered edit operations used when comparing can be reduced in a number of situations. In such cases, the application of the generic Levenshtein distance can result in degraded detection and computational performance. Other metrics in the literature enable limiting the considered edit operations to a smaller subset. However, the possibility where a difference can only result from deleted bytes is not yet explored. To this end, we propose an insert-only variation of the Levenshtein distance to enable comparison of two strings for the case in which differences occur only because of missing bytes. The proposed distance metric is named slice distance and is formally presented and its computational complexity is discussed. We also provide a discussion of the potential security applications of the slice distance.

sted, utgiver, år, opplag, sider
New York: IEEE, 2018. s. 1-5
Emneord [en]
Measurement, Pattern matching, Time complexity, Transforms, Security, DNA
HSV kategori
Forskningsprogram
Datavetenskap
Identifikatorer
URN: urn:nbn:se:kau:diva-67012DOI: 10.1109/NTMS.2018.8328718ISI: 000448864200049ISBN: 978-1-5386-3662-6 (digital)ISBN: 978-1-5386-3663-3 (tryckt)OAI: oai:DiVA.org:kau-67012DiVA, id: diva2:1198286
Konferanse
9th IFIP International Conference on New Technologies, Mobility and Security, 26-28 February 2018, Paris, France
Prosjekter
HITS, 4707
Forskningsfinansiär
Knowledge Foundation, 4707Tilgjengelig fra: 2018-04-17 Laget: 2018-04-17 Sist oppdatert: 2019-11-11bibliografisk kontrollert

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Afzal, ZeeshanGarcia, JohanLindskog, StefanBrunström, Anna

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