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Bio-inspired Hybrid Feature Selection Model for Intrusion Detection
Adel Hamdan Mohammad
,
Tariq Alwada'n
, Omar Almomani
, Sami Smadi
, Nidhal Elomari
Department of Computing & Games
Centre for Digital Innovation
Research output
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Contribution to journal
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Article
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peer-review
418
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Keyphrases
Bio-inspired
100%
Bio-inspired Feature Selection
25%
Evaluation Criteria
25%
Evaluation Purposes
25%
F-measure
50%
Feature Preferences
25%
Feature Selection
25%
Feature Selection Models
100%
Firefly Algorithm
25%
Grey Wolf Optimization
25%
Hybrid Feature Selection
100%
Intrusion Detection
100%
Intrusion Detection System
25%
Multilayer Model
25%
NSL-KDD
25%
Number of Attacks
25%
Optimized Genetic Algorithm
100%
Particle Swarm Optimization
25%
Precision Measure
25%
Precision-recall
25%
Priority Value
100%
Recall Measures
25%
Selective Features
50%
Set-based
50%
Standard Genetic Algorithm
25%
Training Phase
25%
Two-layer
25%
UNSW-NB15
25%
Computer Science
Feature Extraction
100%
Feature Selection
100%
Genetic Algorithm
100%
Grey Wolf Optimization
20%
Intrusion Detection
100%
Intrusion Detection System
20%
Optimization Algorithm
20%
Particle Swarm Optimization
20%
Selection Model
100%
Training Phase
20%
Mathematics
Complex Problem
20%
Genetic Algorithm
100%
Particle Swarm Optimization
20%