A COMPREHENSIVE STUDY OF DEEP LEARNING, TEMPORAL ANALYSIS AND SEMANTIC-ANOMALY SUSION FOR IOT AND IIOT INTRUSION DETECTION /

Lignende værker

• AN ADVERSARIAL APPROACH FOR INTRUSION DETECTION USING DEEP LEARNING /
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• FLOW BASED ANOMALY DETECTION IN SOFTWARE DEFINED NETWORKING: A DEEP LEARNING APPROACH WITH FEATURE SELECTION METHOD
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  Udgivet: (2019)
• FLOW BASED ANOMALY DETECTION IN SOFTWARE DEFINED NETWORKING: A DEEP LEARNING APPROACH WITH FEATURE SELECTION METHOD /
  af: Dey, Samrat Kumar
  Udgivet: (2018)
• AUTOMATIC HAND GESTURE RECOGNITION USING SEMANTIC SEGMENTATION AND DEEP LEARNING /
  af: Chanda, Bristy
  Udgivet: (2025)
• ENHANCED DETECTION AND ANOMALY IDENTIFICATION IN CHIPLESS RFID SYSTEMS USING SCALABLE MACHINE LEARNING MODELS /
  af: Afrin, Farhana
  Udgivet: (2025)