DETECTION OF ANOMALIES BY A COMBINING APPROACH SUPERVISORY AND NON-SUPERVISE LEARNING

摘要

The invention relates to a method for detecting anomalies in a set of transactions established through a telecommunication network, comprising: determining (S1) for each transaction a set of parameter values associated with the transaction; the course (S3), for each transaction, of at least one tree previously defined on a training set, by comparing the values of the parameters with the values associated with each node of said at least one tree, until a leaf is reached; the tree being driven (S2) so that each of the sheets corresponds to a single transaction of the training set and its sheets are each associated with an indication if they correspond to a normal transaction or to an anomaly the determination (S5) of a score according to a first metric depending on the position of the leaf in the tree, and a second metric depending on these indications of the leaves, said score indicating an estimate if the transaction is normal or abnormal.