FLOW BASED ANOMALY DETECTION IN SOFTWARE DEFINED NETWORKING: A DEEP LEARNING APPROACH WITH FEATURE SELECTION METHOD /
Bewaard in:
| Hoofdauteur: | |
|---|---|
| Coauteur: | |
| Formaat: | Boek |
| Taal: | Engels |
| Gepubliceerd in: |
Dhaka :
CSE DEPT MIST ,
c 2018.
|
| Onderwerpen: | |
| Tags: |
Geen labels, Wees de eerste die dit record labelt!
|
Gelijkaardige items: FLOW BASED ANOMALY DETECTION IN SOFTWARE DEFINED NETWORKING: A DEEP LEARNING APPROACH WITH FEATURE SELECTION METHOD /
- FLOW BASED ANOMALY DETECTION IN SOFTWARE DEFINED NETWORKING: A DEEP LEARNING APPROACH WITH FEATURE SELECTION METHOD
- AN ADVERSARIAL APPROACH FOR INTRUSION DETECTION USING DEEP LEARNING /
- DESIGNING SOFTWARE DEFINED RADIO (SDR) FOR SECURED MULTIMODE WIDEBAND OPERATION /
- ENHANCED DETECTION AND ANOMALY IDENTIFICATION IN CHIPLESS RFID SYSTEMS USING SCALABLE MACHINE LEARNING MODELS /
- METAHEURISTIC SEARCH-BASED FEATURE SET SELECTION TECHNIQUES FOR CREDIT CARD FRAUD DETECTION /
- A DEEP LEARNING-BASED APPROACH FOR DETECTING BANGLA SPAM EMAILS /