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...
Saved in:
| Hovedforfatter: | |
|---|---|
| Format: | Thesis |
| Sprog: | engelsk |
| Udgivet: |
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING MILITARY INSTITUTE OF SCIENCE AND TECHNOLOGY
2019
|
| Online adgang: | http://hdl.handle.net/123456789/394 |
| Tags: |
Ingen Tags, Vær først til at tagge denne postø!
|