US 12,293,003 B2
Machine learning modeling to identify sensitive data
Shubhanshu Gupta, Singapore (SG); Ashish Awasthi, Singapore (SG); Amaruvi Devanathan, Chennai (IN); and Mallapu Raghavulu Surya Prakash, Singapore (SG)
Assigned to CITIBANK, N.A., New York, NY (US)
Filed by Citibank, N.A., New York, NY (US)
Filed on May 3, 2024, as Appl. No. 18/654,684.
Application 18/654,684 is a continuation of application No. 17/476,388, filed on Sep. 15, 2021, granted, now 11,977,660.
Prior Publication US 2024/0289492 A1, Aug. 29, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 21/62 (2013.01); G06F 16/22 (2019.01); G06F 16/334 (2025.01); G06F 16/335 (2019.01)
CPC G06F 21/6254 (2013.01) [G06F 16/221 (2019.01); G06F 16/3347 (2019.01); G06F 16/335 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
executing, by a processor, a first artificial intelligence model to generate a first score corresponding a first likelihood of a set of text including personally identifiable information;
executing, by the processor, a second artificial intelligence model to generate a second score corresponding to a second likelihood of the set of text including personally identifiable information, the second artificial intelligence model determining the second score based on a cardinality value or a length value associated with the set of text; and
masking, by the processor, at least a portion of the set of text likely to include personally identifiable information in accordance with the first score and the second score.