Title :

Online EM monitoring of 802.11n networks using Self Adaptive Kernel Machine

Author(s) :

Jonathan, Villain [Auteur]
Centre for Digital Systems [CERI SN - IMT Nord Europe]
Laboratoire Électronique Ondes et Signaux pour les Transports [COSYS-LEOST]
Fleury, Anthony [Auteur]
Université de Lille
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Lille Douai]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Nord Europe]
Centre for Digital Systems [CERI SN - IMT Nord Europe]
Deniau, Virginie [Auteur]
Laboratoire Électronique Ondes et Signaux pour les Transports [COSYS-LEOST]
Gransart, Christophe [Auteur]
Laboratoire Électronique Ondes et Signaux pour les Transports [COSYS-LEOST]
Simon, Eric [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Télécommunication, Interférences et Compatibilité Electromagnétique - IEMN [TELICE - IEMN]

Conference title :

2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA)

City :

Boca Raton

Country :

France

Start date of the conference :

2019-12-16

Book title :

2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA)

Publisher :

IEEE

English keyword(s) :

Classification adaptive approach identification of attacks communication monitoring
Classification
adaptive approach
identification of attacks
communication monitoring

HAL domain(s) :

Informatique [cs]/Traitement du signal et de l'image [eess.SP]

English abstract : [en]

In this work, we evaluated the performances of an adaptive and online clustering algorithm (Self-Adaptive Kernel Machine-SAKM) adjusted for the automatic and online recognition of attacks on wi-fi communication (802.11n ...
Show more >In this work, we evaluated the performances of an adaptive and online clustering algorithm (Self-Adaptive Kernel Machine-SAKM) adjusted for the automatic and online recognition of attacks on wi-fi communication (802.11n protocol). The results presented here are part of a wider project dealing with wi-fi system monitoring. The radio waves are easy to listen. Due to the quick evolution in the available attacks, the use of learning algorithm cannot cover all configurations. Online clustering constructs evolving models without knowledge of the different cases to discriminate and is therefore well suited to this type of problematic. Based on SVM and kernel methods, the SAKM algorithm uses a fast adaptive learning procedure to take into account variations over time.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Institut d'Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520

Source :

Harvested from HAL