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This paper presents a proposal for discovering anomalies in e-banking Web sessions by implementing different datamining techniques in a a graph-based environment. Online banking is a good example of how millions of costumers rely on virtual channels for business transactions. Nevertheless, due to multiple scandals regarding security flaws, it becomes complicated moving a business from a physical scenario to the digital world. Therefore, security applications become highly necessary. Monitoring systems like HIDS intend to create a more reliable scenario for companies but because of the number of sessions linked to e-banking Web servers it is barely impossible to detect fraud in real time. We propose a novel method for detecting anomalies in e-banking services by integrating efficient clustering systems based in sequence alignment and graph mining.
CitationGarcia-Cervigon, M.; Vázquez, J.; Medina, M. Web sessions anomaly detection in dynamic environments. A: Information Security Solutions Europe. "2009 Information Security Solutions Europe". Haya: Vieweg+Teubner, 2010, p. 216-220.
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