Method and device for recognizing anomalies in a data stream of a communication network
OwnerAntonio La Marca, Markus Hanselmann +1inventors
InventorsAntonio La Marca, Markus Hanselmann, Thilo Strauss
Life of this patent
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Abstract
A method for the automatic recognition of anomalies in a data stream in a communication network. The method includes providing a trained variational autoencoder that is trained on non-faulty data packets, with specification of a reference distribution of latent quantities, indicated by reference distribution parameters; determining one or more distribution parameters as a function of an input quantity vector applied to the trained variational autoencoder, which vector is determined by one or more data packets; and recognizing the one or more data packets as anomalous data packet(s) as a function of the one or more distribution parameters.
Claims14
A method for the automatic recognition of anomalies in a data stream in a communication network, comprising:
- providing a trained variational autoencoder that is trained on non-faulty data packets, with specification of a reference distribution of latent quantities, indicated by reference distribution parameters;
- determining one or more distribution parameters as a function of an input quantity vector applied to the trained variational autoencoder, which vector is determined by one or more data packets;
- and
- recognizing the one or more data packets as anomalous data packet(s) as a function of the one or more distribution parameters.
A device for the automatic recognition of anomalies in a data stream in a communication network, the device configured to:
- determine one or more distribution parameters as a function of an input quantity vector applied to a trained variational autoencoder, which vector is determined by one or more data packets, the trained variational autoencoder being trained on non-faulty data packets with a specification of a reference distribution of latent quantities indicated by reference distribution parameters;
- and
- recognize the one or more data packets as anomalous data packets as a function of the one or more distribution parameters.
A non-transitory electronic storage medium on which is stored a computer program for the automatic recognition of anomalies in a data stream in a communication network, the computer program, when executed by a computer, causing the computer to perform:
- providing a trained variational autoencoder that is trained on non-faulty data packets, with specification of a reference distribution of latent quantities, indicated by reference distribution parameters;
- determining one or more distribution parameters as a function of an input quantity vector applied to the trained variational autoencoder, which vector is determined by one or more data packets;
- and
- recognizing the one or more data packets as anomalous data packet(s) as a function of the one or more distribution parameters.
Dependencies are inferred from the claim text.