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Large scale congurable text matching for detection of log changes and anomalies
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Manually analysing logfiles is a very time consuming and error-prone effort. By developing a system to automatically analysing the logfiles it is possible to both increase the speed and accuracy of the analysis. This thesis presents a method for automatic anomaly detection in logfiles using statistical analysis and threshold based classification. The presented method uses five different threshold based approaches to identify anomalous entries within a logfile. Each of the five approaches was successful in identifying and reporting perceived anomalies within 805 logfiles provided by Sandvine, it was however not possible to do a formal evaluation of the results due to a lack of a ground truth.

Place, publisher, year, edition, pages
2019. , p. 64
Keywords [en]
Anomaly Detection, logging, syslog, bootlog, threshold based classification
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kau:diva-72931OAI: oai:DiVA.org:kau-72931DiVA, id: diva2:1329187
External cooperation
Sandvine
Subject / course
Computer Science
Educational program
Engineering: Computer Engineering (300 ECTS credits)
Supervisors
Examiners
Projects
HITS, 4707Available from: 2019-12-05 Created: 2019-06-24 Last updated: 2020-02-20Bibliographically approved

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fulltext(7378 kB)25 downloads
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File name FULLTEXT01.pdfFile size 7378 kBChecksum SHA-512
7eec526c1e0505fce87ebcada087a6d753d8d96febe360e5dc40a0b96bc30ef8c01ee973e25928165bfc07b9e64ebba42839d4fd9c13c6abaaae896a3f598d65
Type fulltextMimetype application/pdf

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf