A Granular Computing Approach for Multi-Labelled Sequences Classification in IEEE 802.11 Networks
Author:
Affiliation:
1. University of Rome “La Sapienza”,Department of Information Engineering, Electronics and Telecommunications,Rome,Italy,00184
2. LUISS University,Department of Business and Management,Rome,Italy,00197
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9891857/9889787/09892473.pdf?arnumber=9892473
Reference27 articles.
1. Intrusion Detection in Wi-Fi Networks by Modular and Optimized Ensemble of Classifiers
2. Transfer-learning-based Network Traffic Automatic Generation Framework
3. Unsupervised Binary BAT algorithm based Network Intrusion Detection System using enhanced multiple classifiers
4. Distributed Intrusion Detection System using Semantic-based Rules for SCADA in Smart Grid
5. Ieee standard for information technology-telecommunications and information exchange between systems local and metropolitan area networks-specific requirements - part 11: Wireless lan medium access control (mac) and physical layer (phy) specifications;IEEE Std 802 11–2016 (Revision of IEEE Std 802 11-2012),2016
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1. Graph-Based Multi-Label Classification for WiFi Network Traffic Analysis;Applied Sciences;2022-11-07
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