Abstract
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.
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Gutiérrez, MC., Pongilupi, J., LLinàs, M. (2010). Web Sessions Anomaly Detection in Dynamic Environments. In: Pohlmann, N., Reimer, H., Schneider, W. (eds) ISSE 2009 Securing Electronic Business Processes. Vieweg+Teubner. https://doi.org/10.1007/978-3-8348-9363-5_21
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DOI: https://doi.org/10.1007/978-3-8348-9363-5_21
Publisher Name: Vieweg+Teubner
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