Anomaly based intrusion detection for 802.11 networks with optimal features using SVM classifier

Wireless Networks

Volumn 23, Issue 8, 2017, Pages 2431-2446

  Usha, M ^a   Kavitha, P ^b  

^a SONA COLLEGE OF TECHNOLOGY   (India)

^b ADHIYAMAAN COLLEGE OF ENGINEERING   (India)

Author keywords

Intrusion detection system; MAC 802.11; Normalized gain (NG); Particle swarm optimization (PSO); Support vector machine (SVM) classifier; WLAN

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); CLUSTERING ALGORITHMS; COMPLEX NETWORKS; COMPUTER CRIME; ECONOMIC AND SOCIAL EFFECTS; INTRUSION DETECTION; LEARNING ALGORITHMS; LEARNING SYSTEMS; MERCURY (METAL); PARTICLE SWARM OPTIMIZATION (PSO); SUPPORT VECTOR MACHINES; WI-FI; WIRELESS TELECOMMUNICATION SYSTEMS;

ANOMALY-BASED INTRUSION DETECTION; COMPUTATION COMPLEXITY; INTRUSION DETECTION SYSTEMS; MAC 802.11; NORMALIZED GAINS; OPTIMAL FEATURE SELECTIONS; SEMI-SUPERVISED CLUSTERING; WLAN;

FEATURE EXTRACTION;

EID: 84969850606     PISSN: 10220038     EISSN: 15728196     Source Type: Journal    
DOI: 10.1007/s11276-016-1300-5     Document Type: Article

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