Detection of cyber-attacks on Wi-Fi networks by classification of spectral data

Villain, Jonathan; Deniau, Virginie; Fleury, Anthony; Gransart, Christophe; Simon, Eric

Document type :

Communication dans un congrès avec actes

DOI :

10.23919/URSIGASS49373.2020.9232196

Title :

Detection of cyber-attacks on Wi-Fi networks by classification of spectral data

Author(s) :

Villain, Jonathan [Auteur]
Laboratoire Électronique Ondes et Signaux pour les Transports [COSYS-LEOST ]
Deniau, Virginie [Auteur]
Laboratoire Électronique Ondes et Signaux pour les Transports [COSYS-LEOST ]
Fleury, Anthony [Auteur]
Centre for Digital Systems [CERI SN - IMT Nord Europe]
Gransart, Christophe [Auteur]
Laboratoire Électronique Ondes et Signaux pour les Transports [COSYS-LEOST ]
Simon, Eric [Auteur]

Télécommunication, Interférences et Compatibilité Electromagnétique - IEMN [TELICE - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]

Conference title :

33rd General Assembly and Scientific Symposium of the International-Union-of-Radio-Science

City :

Rome

Country :

Italie

Start date of the conference :

2020-08-29

Book title :

33rd General Assembly and Scientific Symposium of the International-Union-of-Radio-Science

Publisher :

IEEE

Publication date :

2020

HAL domain(s) :

Sciences de l'ingénieur [physics]

English abstract : [en]

In many areas, communications or computer networks include both wired and wireless sections. In this research, we are interested in the wireless network sections. This part of the networks can targeted by denial of service ...
Show more >In many areas, communications or computer networks include both wired and wireless sections. In this research, we are interested in the wireless network sections. This part of the networks can targeted by denial of service attacks, affecting the reception quality of communication signals, or by "man-in-the-loop" attacks aiming to intercept information. This paper presents a work based on the analysis of wireless electromagnetic activity to detect such attacks against an IEEE 802.11n Wi-Fi network. The approach is based on the analysis of spectral occupation by classification technics. Experimentations were performed in anechoic chamber in applying jamming attacks and de authentication attacks. In a first step, in performing the Principal component analysis of the spectra measured for the different tested situations, we analyse if the different classes can be separated. In a second step, we assess the ability of a Self Adaptative Kernel Machine to classify the different attacks without a preliminary learning phase of the attack situations.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

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