Network intrusion detection system using Deep learning Approach – B.Sc. Senait Molla Meressa, BSc
B.Sc. Senait Molla Meressa, BSc
Master's thesis
Network intrusion detection system using Deep learning Approach
Abstract:
The increasing rate of network attacks is a concerning issue that affects the availability, confidentiality, and integrity of data. To detect malicious cyberattacks, one should require a genuine security system that automates the process of monitoring the events that occur in a network. In this thesis, an anomaly intrusion detection system has been studied and modeled based on a deep learning approach …more
Language used: English
Date on which the thesis was submitted / produced: 31. 3. 2021
Thesis defence
- Supervisor: Ing. Tomáš Vokoun
Citation record
ISO 690-compliant citation record:
MERESSA, Senait Molla. \textit{Network intrusion detection system using Deep learning Approach}. Online. Master's thesis. Praha: Czech University of Life Sciences Prague, Faculty of Economics and Management. 2021. Available from: https://theses.cz/id/za4zo6/.
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Published in Theses:- světu
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Institution archiving the thesis and making it accessible: Česká zemědělská univerzita v Praze, Provozně ekonomická fakultaCzech University of Life Sciences Prague
Faculty of Economics and ManagementMaster programme / field:
Systems Engineering and Informatics / Informatics
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