A COMPREHENSIVE STUDY OF DEEP LEARNING, TEMPORAL ANALYSIS AND SEMANTIC-ANOMALY SUSION FOR IOT AND IIOT INTRUSION DETECTION /
Shranjeno v:
| Glavni avtor: | |
|---|---|
| Korporativna značnica: | |
| Format: | Knjiga |
| Jezik: | angleščina |
| Izdano: |
Dhaka :
EECE DEPT. MIST,
c2026.
|
| Teme: | |
| Oznake: |
Brez oznak, prvi označite!
|
Podobne knjige/članki: A COMPREHENSIVE STUDY OF DEEP LEARNING, TEMPORAL ANALYSIS AND SEMANTIC-ANOMALY SUSION FOR IOT AND IIOT INTRUSION DETECTION /
- AN ADVERSARIAL APPROACH FOR INTRUSION DETECTION USING DEEP LEARNING /
- 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 /
- AUTOMATIC HAND GESTURE RECOGNITION USING SEMANTIC SEGMENTATION AND DEEP LEARNING /
- A COMPARATIVE BEHAVIOURAL STUDY OF MACHINE LEARNING AND DEEP LEARNING MODELS FOR NETWORK INTRUSION DETECTION ACROSS DATASETS OF DIFFERING STATISTICAL CHARACTER /
- ENHANCED DETECTION AND ANOMALY IDENTIFICATION IN CHIPLESS RFID SYSTEMS USING SCALABLE MACHINE LEARNING MODELS /