| CPC H04L 63/1433 (2013.01) | 15 Claims |
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1. A cybersecurity method for determining exploits, comprising the steps of:
receiving a graph representing a digital network of a plurality of nodes forming a federated learning network, the graph including at least one vulnerability for each of the plurality of nodes;
receiving, for the plurality of nodes, a plurality of embeddings based on the graph, wherein the plurality of embeddings include a vector of real numbers representing the plurality of notes in the graph;
assigning an agent an initial node from the plurality of nodes;
querying the graph to obtain a plurality of accessible nodes and at least one vulnerability for the accessible nodes;
determining a transition for the agent to take from the initial node to a next accessible node from the plurality of accessible nodes;
computing using a neural network, a reward for moving to the next accessible node;
assigning the agent a new state corresponding to the next accessible node;
collecting, by a collected experience database, a history of node assignments of the agent, a plurality of connections taken by the agent, and a plurality of rewards the agent received for transitioning across the plurality of connections;
updating a plurality of parameters of a neural network using the data collected by the collected experience database, wherein the information collected by each of a plurality of agents is used to further update the plurality of parameters of the neural network while not sharing graph data contributed by a plurality of graphs; and
determining, by the agent, what action from a plurality of available actions to take next using the neural network.
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