1. A method for the detection of anomalous behaviors in a computer network, comprising the steps of: collecting data relating to connections initiated by components in the network, said components selected from any one or more of a group including users, nodes and applications, sending said data to an anomaly detection system (ADS) platform, computing from said data an anomaly level of each component or of each of a group of said components, and computing a multidimensional chart for visualizing the behavior of said components or groups of components in said network in which said anomaly level of said components or groups of components is represented on a dimension in said chart.