US 12,107,837 B2
Cloud based machine learning notebook data loss prevention
Hari Bhaskar Sankaranarayanan, Bangalore (IN); and Jean-Rene Gauthier, Temecula, CA (US)
Assigned to Oracle International Corporation, Redwood Shores, CA (US)
Filed by Oracle International Corporation, Redwood Shores, CA (US)
Filed on Apr. 7, 2022, as Appl. No. 17/715,650.
Prior Publication US 2023/0328037 A1, Oct. 12, 2023
Int. Cl. H04L 9/40 (2022.01); G06F 21/60 (2013.01); G06N 5/022 (2023.01)
CPC H04L 63/04 (2013.01) [G06F 21/602 (2013.01); G06N 5/022 (2013.01); H04L 63/1433 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method of securing data on a cloud based network that comprises one or more machine learning (ML) notebooks, the method comprising:
monitoring activity on each of the ML notebooks, wherein each of the ML notebooks comprise an interactive ML software environment with a plurality of cells, the activity comprising one or more commands executed within one or more of the plurality of cells;
classifying each of the commands, the classifying comprising generating input parameters, the input parameters comprising at least one of a type of command, a type of data used in the command, or a type of activity;
based on the input parameters, determining a data security risk score for each of the ML notebooks; and
when the data security risk score exceeds a predetermined threshold, generating a data security alert.