FLOW BASED ANOMALY DETECTION IN SOFTWARE DEFINED NETWORKING: A DEEP LEARNING APPROACH WITH FEATURE SELECTION METHOD
I am precisely thankful to Almighty for his unceasing and immense blessings without which my thesis completion would remain scattered and incomplete. I express my heartiest gratitude, profound indebtedness and deep respect to my supervisor, Dr. Md. Mahbubur Rahman, Professor, Department of CSE, M...
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| Format: | Abschlussarbeit |
| Sprache: | Englisch |
| Veröffentlicht: |
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING MILITARY INSTITUTE OF SCIENCE AND TECHNOLOGY
2019
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| Online-Zugang: | http://hdl.handle.net/123456789/394 |
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| Zusammenfassung: | I am precisely thankful to Almighty for his unceasing and immense blessings without
which my thesis completion would remain scattered and incomplete. I express my
heartiest gratitude, profound indebtedness and deep respect to my supervisor, Dr. Md.
Mahbubur Rahman, Professor, Department of CSE, Military Institute of Science and
Technology, for his constant supervision, affectionate guidance and great encouragement
and motivation. His keen interest on the topic and valuable advices throughout the study
was of great help in completing thesis.
I am especially grateful to the Department of Computer Science and Engineering of
Military Institute of Science and Technology (MIST) for providing their all out support
during the thesis work.
Finally, I would like to thank my parents, family members and friends for their
appreciable assistance, patience and suggestions during the course of my thesis. |
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