BUILDING MULTI-REPRESENTATIONAL LEARNING MODELS FOR STATIC ANALYSIS OF SOURCE CODE

Patent №

US 11,615,184

Granted

2023-03-28

Filed 2020

Owner

PALO ALTO NETWORKS, INC.

Lab

AI components

4

ml · nlp · vision · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

16779271

A system/process/computer program product for building multi-representational learning models for static analysis of source code includes receiving training data, wherein the training data includes a set of source code files for training a multi-representational learning (MRL) model for classifying malicious source code and benign source code based on a static analysis; generating a first feature vector based on a set of characters extracted from the set of source code files; generating a second feature vector based on a set of tokens extracted from the set of source code files; and performing an ensemble of the first feature vector and the second feature vector to form a target feature vector for classifying malicious source code and benign source code based on the static analysis.

Machine learningNatural languageVisionAI hardwareG06F 21/563G06F 8/42G06F 8/75G06F 18/24G06F 18/24143G06F 21/577G06N 3/045G06N 3/0464+6 more

AI classification

Machine learning1.00
AI hardware0.99
Natural language0.96
Vision0.93
Planning0.10
Knowledge representation0.02
Evolutionary computation0.00
Speech0.00

Ownership

PALO ALTO NETWORKS, INC.

assignment · 520540263

Assignors

KUTT, BRODY JAMES, HEWLETT II, WILLIAM REDINGTON, STAROV, OLEKSII, ZHOU, YUCHEN, LIU, FANG

On an employer assignment, the assignors are typically the inventors.

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