Robert Boschgmbh

Katharina Dormann

Thilo Strauss

Markus Hanselmann

Holger Ulmer

Andrej Junginger

Jens Stefan Buchner

Sebastian Boblest

A device and a computer-implemented method for classifying data, in particular for a Controller Area Network or an automotive Ethernet network. A plurality of messages is received from a communications network. A message that has a predefined message type is selected for an input variable for an input model of a plurality of input models of an artificial neural network associated with the predefined message type. The input variable is determined as a function of the message, and in an output area of the artificial neural network a prediction is output that is usable for classifying the message as a function of the input variable, or a reconstruction of an input variable is output that is usable for classifying the message as a function of this input variable.

Device and method for classifying data in particular for a controller area network or an automotive ethernet network

An apparatus and a method for calibrating a system for recognizing attempts to penetrate into a computer network, in particular of a motor vehicle, at least one parameter being estimated on the basis of a data set, the data set encompassing values that characterize a detected occurrence of messages in the computer network; a distribution function being determined on the basis of the at least one parameter; an inverse of the distribution function being determined; and at least one limit for the values being calibrated, on the basis of the inverse, in a rule for rule-based recognition of attempts to penetrate into the computer network.

Method and apparatus for calibrating a system for recognizing attempts to penetrate a computer network

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Heidelberg, Germany

Katharina Dormann