IEEE 802.11 network anomaly detection and attack classification: A deep learning approach

IEEE Wireless Communications and Networking Conference, WCNC

Volumn , Issue , 2017, Pages

  Thing, Vrizlynn L L ^a  

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

Author keywords

Anomaly detection; Attack classification; Deep learning; IEEE 802.11 attacks; IoT security

Indexed keywords

STANDARDS; WIRELESS TELECOMMUNICATION SYSTEMS;

ANOMALY DETECTION; ATTACK CLASSIFICATIONS; CLASSIFICATION SYSTEM; IEEE 802.11 NETWORKS; IEEE 802.11S; IOT SECURITY; MULTI-CLASS PROBLEMS; WIRELESS TECHNOLOGIES;

DEEP LEARNING;

EID: 85019760246     PISSN: 15253511     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WCNC.2017.7925567     Document Type: Conference Paper

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