Patent ID: 11962661
Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
Field: Digital communication (Electrical engineering)
Classification: CPC H  G | IPC G  H

Claim 0:
1. A method for training a graph neural network for use in controlling interaction with a computing network, comprising:
identifying a plurality of entities that interact with the computing network, each of which is determined to exhibit a prescribed amount of network activity;
associating respective nodes with the entities;
identifying respective feature sets for the plurality of entities, each feature set including features that describe network activity exhibited by an associated entity;
identifying a plurality of edges, each edge in the plurality of edges connecting two entities in the plurality of entities having feature sets that satisfy a prescribed test for similarity;
labeling at least some of the entities with labels, each label indicating whether a corresponding entity is a kind of entity that engages in abusive network-related activity in collaboration with other entities that also engage in the abusive network-related activity, with respect to a given standard that defines what constitutes abusive network-related activity,
the nodes, edges, and labels defining a training set;
training the graph neural network based on the training set, to provide a trained graph neural network; and
configuring an abuse control system using the trained graph neural network to detect and act on abusive network-related activity in the computing network.