Unsupervised Anomaly- and Outlier Detection in Network Metrics 2020 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis

Place, publisher, year, edition, pages

2020. , p. 57

Keywords [en]

Anomaly detection, outlier detection, ARIMA, DBSCAN, LSTM, Au-toencoder, moving average, network metric analysis

National Category

Computer Sciences

Identifiers

URN: urn:nbn:se:ltu:diva-80471OAI: oai:DiVA.org:ltu-80471DiVA, id: diva2:1459387

External cooperation

Netrounds AB

Subject / course

Student thesis, at least 30 credits

Educational program

Computer Science and Engineering, master's level

Supervisors

Examiners

Available from: 2020-08-28 Created: 2020-08-19 Last updated: 2020-08-28Bibliographically approved

Open Access in DiVA

No full text in DiVA

By organisation

Department of Computer Science, Electrical and Space Engineering

On the subject

Computer Sciences

Search outside of DiVA

GoogleGoogle ScholarTotal: 138 hits