A COMPREHENSIVE STUDY OF DEEP LEARNING, TEMPORAL ANALYSIS AND SEMANTIC-ANOMALY SUSION FOR IOT AND IIOT INTRUSION DETECTION /
में बचाया:
| मुख्य लेखक: | |
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| निगमित लेखक: | |
| स्वरूप: | पुस्तक |
| भाषा: | अंग्रेज़ी |
| प्रकाशित: |
Dhaka :
EECE DEPT. MIST,
c2026.
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| विषय: | |
| टैग: |
कोई टैग नहीं, इस रिकॉर्ड को टैग करने वाले पहले व्यक्ति बनें!
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समान संसाधन: 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 /