CODE ANALYSIS FOR PRIVACY AND RISK ASSESSMENT USING A TRAINED MACHINE-LEARNING MODEL

Number of patents in Portfolio can not be more than 2000

United States of America

APP PUB NO 20250117480A1
SERIAL NO

18484058

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Abstract

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Systems and methods for code analysis are provided. A system receives, from a first data owner system, an input indicating one or more privacy constraints, wherein the one or more privacy constraints indicate one or more rules for operating on a sensitive data set in a data store associated with the first data owner system. The system receives data comprising code configured to operate on the sensitive data set. The system apples a first set of one or more machine-learning-trained models to process the first input and the data comprising the code to generate code analysis output data, wherein the code analysis output data comprises an indication of whether the code satisfies the one or more privacy constraints. The system generates and transmits, based on the code analysis output data, an instruction indicating whether to execute the code to operate on the sensitive data.

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Patent Owner(s)

Patent OwnerAddress
CHOPRA KARTIK135 YORK STREET APT 745 BROOKLYN NY 11201

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
CHOPRA, Kartik New York, US 4 0
ROY, Sidhartha Cambridge, US 4 0
WAGH, Sameer Jersey City, US 5 28

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