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...
Tallennettuna:
| Päätekijä: | |
|---|---|
| Aineistotyyppi: | Opinnäyte |
| Kieli: | englanti |
| Julkaistu: |
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING MILITARY INSTITUTE OF SCIENCE AND TECHNOLOGY
2019
|
| Linkit: | http://hdl.handle.net/123456789/394 |
| Tagit: |
Ei tageja, Lisää ensimmäinen tagi!
|