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Conference papers

Detecting Anomalies in Data Streams using Statecharts (Demo)

Vasile-Marian Scuturici 1, 2 Dan-Mircea Suciu Romain Vuillemot 2, 1 Aris Ouksel Lionel Brunie 1
1 DRIM - Distribution, Recherche d'Information et Mobilité
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
2 BD - Base de Données
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Résumé : The environment around us is progressively equipped with various sensors, producing data continuously. The applications using these data face many challenges, such as data stream integration over an attribute (such as time) and knowledge extraction from raw data. In this paper we propose one approach to face those two challenges. First, data streams integration is performed using statecharts which represents a resume of data produced by the corresponding data producer. Second, we detect anomalous events over temporal relations among statecharts. We describe our approach in a demonstration scenario, that is using a visual tool called Patternator.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01381632
Contributor : Équipe Gestionnaire Des Publications Si Liris Connect in order to contact the contributor
Submitted on : Friday, October 14, 2016 - 2:50:43 PM
Last modification on : Monday, August 30, 2021 - 2:24:01 PM

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  • HAL Id : hal-01381632, version 1

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Vasile-Marian Scuturici, Dan-Mircea Suciu, Romain Vuillemot, Aris Ouksel, Lionel Brunie. Detecting Anomalies in Data Streams using Statecharts (Demo). Extraction et Gestion des Connaissances (EGC'10), Jan 2010, Hammamet, Tunisie. pp.635-636. ⟨hal-01381632⟩

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