CPC H04L 63/1433 (2013.01) [G06F 21/577 (2013.01); G06F 40/295 (2020.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01)] | 20 Claims |
1. A computer-implemented method comprising:
processing a plurality of risk reports corresponding to a plurality of network devices in a network to determine a multidimensional risk score for the network;
analyzing the plurality of risk reports using a semantic analysis model to identify one or more factors that contribute to the multidimensional risk score;
determining one or more actions using a trained learning model to mitigate one or more dimensions of the multidimensional risk score, wherein the trained learning model comprises a generative adversarial network that is trained using training data that includes text of risk reports and an ontology that represents a hierarchical relationship between devices, predefined conditions, and symptoms of problems associated with one or more network device of the plurality of network devices; and
presenting outcomes of applying the one or more actions to a user to indicate an effect of each of the one or more actions on the multidimensional risk score for the network.
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