Invention Grant
- Patent Title: Overly optimistic data patterns and learned adversarial latent features
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Application No.: US18379019Application Date: 2023-10-11
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Publication No.: US12323440B2Publication Date: 2025-06-03
- Inventor: Scott Michael Zoldi , Shafi Ur Rahman
- Applicant: FAIR ISAAC CORPORATION
- Applicant Address: US MN Minneapolis
- Assignee: FAIR ISAAC CORPORATION
- Current Assignee: FAIR ISAAC CORPORATION
- Current Assignee Address: US MN Minneapolis
- Agency: Mintz, Levin, Cohn, Ferris, Glovsky and Popeo, P.C.
- Agent F. Jason Far-hadian, Esq.
- Main IPC: H04L9/40
- IPC: H04L9/40 ; G06N3/04 ; G06N3/08

Abstract:
Systems for improving security of a computer-implemented artificial intelligence by monitoring one or more transactions received by the machine learning decision model; receiving a first score generated by the machine learning decision model in association with a first transaction; identifying the first transaction as belonging to a first class, in response to the first score being lower than a certain score threshold and the first transaction having a low occurrence likelihood; receiving a second score in association with the first transaction based on one or more adversarial latent features associated with the first transaction as detectable by an adversary detection model; and determining at least one adversarial latent transaction feature being exploited by the first transaction, in response to determining that the second score falls above the certain score threshold.
Public/Granted literature
- US20240039934A1 OVERLY OPTIMISTIC DATA PATTERNS AND LEARNED ADVERSARIAL LATENT FEATURES Public/Granted day:2024-02-01
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