Characterization of IEEE 802.11 communications ...
Document type :
Article dans une revue scientifique: Article original
Title :
Characterization of IEEE 802.11 communications and detection of low power jamming attacks in noncontrolled environment based on a clustering study
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 ]
Gransart, Christophe [Auteur]
Laboratoire Électronique Ondes et Signaux pour les Transports [COSYS-LEOST ]
Fleury, Anthony [Auteur]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Lille Douai]
Simon, Eric [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Télécommunication, Interférences et Compatibilité Electromagnétique - IEMN [TELICE - IEMN]
Laboratoire Électronique Ondes et Signaux pour les Transports [COSYS-LEOST ]
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 ]
Fleury, Anthony [Auteur]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Lille Douai]
Simon, Eric [Auteur]

Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Télécommunication, Interférences et Compatibilité Electromagnétique - IEMN [TELICE - IEMN]
Journal title :
IEEE Systems Journal
Pages :
pp 683 - 692
Publisher :
IEEE
Publication date :
2022-03
ISSN :
1937-9234
Keyword(s) :
INTERFERENCE ELECTROMAGNETIQUE
TELECOMMUNICATION
TECHNOLOGIE SANS FIL
ONDE
BROUILLEUR
DETECTION
TRAITEMENT DU SIGNAL
TELECOMMUNICATION
TECHNOLOGIE SANS FIL
ONDE
BROUILLEUR
DETECTION
TRAITEMENT DU SIGNAL
English keyword(s) :
IEMI
INTENTIONAL ELECTROMAGNETIC INTERFERENCE
CLASSIFICATION
WLAN
WI-FI
COMMUNICATION NETWORK JOURNAL
IEEE 802.11N.
INTENTIONAL ELECTROMAGNETIC INTERFERENCE
CLASSIFICATION
WLAN
WI-FI
COMMUNICATION NETWORK JOURNAL
IEEE 802.11N.
HAL domain(s) :
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
English abstract : [en]
Wireless connections are more and more used in different applications and in public areas for services to consumers but also for handling (sometimes) sensitive communications (for instance in railway systems or for remote ...
Show more >Wireless connections are more and more used in different applications and in public areas for services to consumers but also for handling (sometimes) sensitive communications (for instance in railway systems or for remote video monitoring systems). Such systems can have to face different kind of attacks that target the behind service. Our work aims to detect, as soon as possible and online, attacks that can occur on wireless networks, to be able to react very quickly. In this paper, we present some results of data analysis methods, on Wi-Fi signals, to differentiate the ones with attacks from the ones without. This study focuses on low power jamming attacks with a slight or even no impact on Wi-Fi communications. This is more challenging than detecting high power jamming attacks which have already been addressed in the literature. Being able to detect a low impact attack is a crucial issue in a global security strategy, making it possible to launch countermeasures before the interruption of the communication. The Wi-Fi bands are also in the ISM frequencies, making the environment complicated to analyze. Clustering methods such as Agglomerative Hierarchical Clustering are used to identify some clusters and then to map them to the real classes (with or without attacks). A deep analysis of the clusters obtained in a dataset acquired in uncontrolled conditions is carried out. This is done in order to understand what is responsible of the clustering assignment of the different points and to extract the clusters which can be used to design a detection attack strategy.Show less >
Show more >Wireless connections are more and more used in different applications and in public areas for services to consumers but also for handling (sometimes) sensitive communications (for instance in railway systems or for remote video monitoring systems). Such systems can have to face different kind of attacks that target the behind service. Our work aims to detect, as soon as possible and online, attacks that can occur on wireless networks, to be able to react very quickly. In this paper, we present some results of data analysis methods, on Wi-Fi signals, to differentiate the ones with attacks from the ones without. This study focuses on low power jamming attacks with a slight or even no impact on Wi-Fi communications. This is more challenging than detecting high power jamming attacks which have already been addressed in the literature. Being able to detect a low impact attack is a crucial issue in a global security strategy, making it possible to launch countermeasures before the interruption of the communication. The Wi-Fi bands are also in the ISM frequencies, making the environment complicated to analyze. Clustering methods such as Agglomerative Hierarchical Clustering are used to identify some clusters and then to map them to the real classes (with or without attacks). A deep analysis of the clusters obtained in a dataset acquired in uncontrolled conditions is carried out. This is done in order to understand what is responsible of the clustering assignment of the different points and to extract the clusters which can be used to design a detection attack strategy.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
European Project :
Source :
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