DEVICE AND METHOD FOR DETERMINING ADVERSARIAL PERTURBATIONS OF A MACHINE LEARNING SYSTEM

• Main Authors: Finnie, Nicole Ying, Hutmacher, Robin, Metzen, Jan Hendrik
• Format: Patent
• Language: English
• Published: 28.12.2023
• Subjects: CONTROL OR REGULATING SYSTEMS IN GENERAL; CONTROLLING; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS; PHYSICS; REGULATING

A computer-implemented method for determining an adversarial perturbation for input signals, especially sensor signals or features of sensor signals, of a machine learning system. A best perturbation is determined iteratively, wherein the best perturbation is provided as adversarial perturbation after a predefined amount of iterations, wherein at least one iteration includes: sampling a perturbation; applying the sampled perturbation to an input signal thereby determining a potential adversarial example; determining an output signal from the machine learning system for the potential adversarial example, determining a loss value characterizing a deviation of the output signal to a desired output signal, wherein the desired output signal corresponds to the input signal, if the loss value is larger than a previous loss value setting the best perturbation to the sampled perturbation.