Patent ID: 11916937
Assignee: UAB 360 IT
Field: Computer technology (Electrical engineering)
Classification: CPC H  G | IPC G  H

Claim 4:
5. A method for malware detection, the method comprising:
performing, on a plurality of user devices, a behavioral analysis of an executable file downloaded to a user device, wherein performance of the behavioral analysis includes: breaking the executable file into a plurality of chunks; and extracting at least one behavioral feature from the plurality of chunks;
classify the chunks based on the behaviors;
score the chunks based on the behaviors;
determine at least one label of maliciousness of the executable file based on the scores of the chunks;
receiving the at least one label of maliciousness of the executable file based on the performance of the behavioral analysis;
receiving a plurality of features extracted from the executable file;
training at least one machine learning model, on a central server in communication with the plurality of user device, based on the plurality of features and the at least one label of maliciousness;
distributing the at least one trained machine learning model to the plurality of user devices; and
updating a machine learning model used for the behavioral analysis with the distributed at least one trained machine learning model.