A COMPARATIVE BEHAVIOURAL STUDY OF MACHINE LEARNING AND DEEP LEARNING MODELS FOR NETWORK INTRUSION DETECTION ACROSS DATASETS OF DIFFERING STATISTICAL CHARACTER /

Lignende værker

• AN ADVERSARIAL APPROACH FOR INTRUSION DETECTION USING DEEP LEARNING /
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• DEEP LEARNING BASED MULTIPLE OBJECT DETECTION AND DISTANCE MANAGEMENT FROM CUSTOM-BUILT DATASET WITH HETEROGENIOUS TRAFFIC /
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  Udgivet: (2023)
• Deep learning /
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• ADAPTIVE AND AGGREGATED MODEL FUSION FOR FEDERATED INTRUSION DETECTION IN HETEROGENEOUS EDGE NETWORKS /
  af: RAFID, SHADMAN
  Udgivet: (2025)
• A COMPREHENSIVE STUDY OF DEEP LEARNING, TEMPORAL ANALYSIS AND SEMANTIC-ANOMALY SUSION FOR IOT AND IIOT INTRUSION DETECTION /
  af: Simin, Zakia Sultana
  Udgivet: (2026)