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User and Entity Behavior Anomaly Detection using Network Traffic
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Place, publisher, year, edition, pages
2017. , 52 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:bth-14636OAI: oai:DiVA.org:bth-14636DiVA: diva2:1113229
External cooperation
SecureLink Sweden AB
Subject / course
Degree Project in Master of Science in Engineering 30.0
Educational program
DVACD Master of Science in Computer Security
Supervisors
Examiners
Available from: 2017-06-21 Created: 2017-06-21 Last updated: 2017-06-21Bibliographically approved

Open Access in DiVA

fulltext(612 kB)48 downloads
File information
File name FULLTEXT02.pdfFile size 612 kBChecksum SHA-512
07daebc9eebc6640c741c33024400e8afa244334f24b8afca0c9b7a2780b93642c2e1e1a61520e12386df78c718256c4abcd8a0cc474c720a503f82896e1ba91
Type fulltextMimetype application/pdf

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
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Output format
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