Rogue behavior detection in NoSQL graph databases

Abstract : Rogue behaviors refer to behavioral anomalies that can occur in human activi- ties and that can thus be retrieved from human generated data. In this paper, we aim at showing that NoSQL graph databases are a useful tool for this pur- pose. Indeed these database engines exploit property graphs that can easily represent human and object interactions whatever the volume and complexity of the data. These interactions lead to fraud rings in the graphs in the form of sophisticated chains of indirect links between fraudsters representing successive transactions (money, communications, etc.) from which rogue behaviours are detected. Our work is based on two extensions of such NoSQL graph databases. The first extension allows the handling of time-variant data while the second one is devoted to the management of imprecise queries with a DSL (to define flexible operators and operations with Scala) and the Cypherf declarative flex- ible query language over NoSQL graph databases. These extensions allow to better address and describe sophisticated frauds. Feasibility have been studied to assess our proposition.
Type de document :
Article dans une revue
Journal of Innovation in Digital Ecosystems, Elsevier 2016, 3 (2), pp.70-82. 〈10.1016/j.jides.2016.10.004〉
Liste complète des métadonnées

Littérature citée [39 références]  Voir  Masquer  Télécharger
Contributeur : Anne Laurent <>
Soumis le : vendredi 18 novembre 2016 - 10:15:28
Dernière modification le : jeudi 18 octobre 2018 - 19:18:43
Document(s) archivé(s) le : mardi 21 mars 2017 - 13:39:43


Rogue Behavior.pdf
Fichiers produits par l'(les) auteur(s)




Arnaud Castelltort, Anne Laurent. Rogue behavior detection in NoSQL graph databases. Journal of Innovation in Digital Ecosystems, Elsevier 2016, 3 (2), pp.70-82. 〈10.1016/j.jides.2016.10.004〉. 〈lirmm-01398978〉



Consultations de la notice


Téléchargements de fichiers