DETECTION OF ANOMALIES BY AN APPROACH COMBINING SUPERVISED AND NON-SUPERVISED LEARNING

摘要

The invention relates to a method for the detection of anomalies in a set of transactions established through a telecommunication network, comprising the determination (S1) for each transaction of a set of parameter values associated with the transaction; the traversal (S3), for each transaction, of at least one tree previously defined on a training suite, 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 trained (S2) so that each of the leaves corresponds to a single transaction of the training suite and that its leaves are each associated with an indication whether they correspond to a normal or anomalous transaction, the determination (S5) of a score as a function of a first metric depending on the position of the leaf in the tree, and of a second metric depending on these indications of the leaves, said score indicating an estimation whether the transaction is normal or anomalous.