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기록

MALICIOUS WEBSITE DETECTION USING INTERMEDIATE REPRESENTATIONS

발명심사 중
2조회수
20청구항 · 2 독립항
§ Ⅰ

개요

발명자

William Ryan Briguglio; Issa Traore; Marcelo Luiz Brocardo

IPC 분류

H4L 9/40

CPC 분류

H4L63/1483

Websites are classified based on intermediate representations of the associated source code using a machine learning model applied to a set of intermediate representations from websites having predetermined classifications. The use of intermediate representations can provide a machine independent classifier that does not required use of lists of websites known to be malicious. The intermediate representation-based classifier can be combined with URL and HTML based classifiers, including classifiers that incorporate URLs that are both statically and dynamically linked.

원문 (중국어)

Websites are classified based on intermediate representations of the associated source code using a machine learning model applied to a set of intermediate representations from websites having predetermined classifications. The use of intermediate representations can provide a machine independent classifier that does not required use of lists of websites known to be malicious. The intermediate representation-based classifier can be combined with URL and HTML based classifiers, including classifiers that incorporate URLs that are both statically and dynamically linked.