Rogue behavior detection in NoSQL graph databases - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Journal Articles Journal of Innovation in Digital Ecosystems Year : 2016

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.
Fichier principal
Vignette du fichier
Rogue Behavior.pdf (1.92 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

lirmm-01398978 , version 1 (18-11-2016)

Identifiers

Cite

Arnaud Castelltort, Anne Laurent. Rogue behavior detection in NoSQL graph databases. Journal of Innovation in Digital Ecosystems, 2016, 3 (2), pp.70-82. ⟨10.1016/j.jides.2016.10.004⟩. ⟨lirmm-01398978⟩
165 View
340 Download

Altmetric

Share

Gmail Facebook X LinkedIn More