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Partial Signature Matching in an MPTCP World using Insert-only Levenshtein Distance
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science. (PriSec)
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science. (DISCO)
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science. (PriSec)
(English)Manuscript (preprint) (Other academic)
Abstract [en]

This paper proposes a methodology consisting of a constrained version of the Levenshtein distance that can be used to detect signatures from partial traffic. The proposed algorithm is formally presented, implemented, and tested using the latest available version of the Snort ruleset. The results show that the algorithm can successfully detect all partial signatures with nearly 90% accuracy.

National Category
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-48173OAI: oai:DiVA.org:kau-48173DiVA: diva2:1082818
Available from: 2017-03-17 Created: 2017-03-17 Last updated: 2017-03-17
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • de-DE
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