Nowadays, the Web has evolved into a mandatory business channel. 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 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.