Utilize este identificador para referenciar este registo: http://hdl.handle.net/1822/10661

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dc.contributor.authorBaras, Karolina-
dc.contributor.authorMoreira, Adriano-
dc.date.accessioned2010-06-14T10:45:18Z-
dc.date.available2010-06-14T10:45:18Z-
dc.date.issued2010-
dc.identifier.citationIEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS, 8, Mahnnheim, Germany, 2010 - International Conference on Pervasive Computing and Communications : PerCom 2010”. New York : IEEE Computer Society Press, 2010. ISBN 978-1-4244-6605-4. p. 202-207.por
dc.identifier.isbn978-1-4244-6605-4-
dc.identifier.urihttp://hdl.handle.net/1822/10661-
dc.description.abstractThis paper focuses on a set of anomaly detection techniques based on the analysis of WiFi access point utilization patterns. The aim is to explore the possibilities of detecting patterns that diverge from the usual ones in spaces covered by wireless networks. In this way special events or happenings in physical places could be identified and fed to a world model as an additional source of information for context-aware applications to use.por
dc.description.sponsorshipFundação para a Ciência e a Tecnologia (FCT)por
dc.language.isoengpor
dc.publisherIEEEpor
dc.rightsrestrictedAccesspor
dc.subjectAnomaly detectionpor
dc.subjectWiFi networkpor
dc.subjectSpace modelingpor
dc.titleAnomaly detection in University Campus WiFi Zonespor
dc.typearticlepor
dc.peerreviewedyespor
Aparece nas coleções:DSI - Sistemas de Computação e Comunicações
CAlg - Artigos em revistas internacionais/Papers in international journals

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