The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 20, 2024

Filed:

Mar. 15, 2021
Applicant:

Netskope, Inc., Santa Clara, CA (US);

Inventors:

Yi Zhang, Santa Clara, CA (US);

Xiaolin Wang, San Jose, CA (US);

Siying Yang, Cupertino, CA (US);

Krishna Narayanaswamy, Saratoga, CA (US);

Assignee:

Netskope, Inc., Santa Clara, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06T 3/4046 (2024.01); G06F 18/214 (2023.01); G06N 3/084 (2023.01); G06N 5/046 (2023.01); G06T 5/50 (2006.01); G06V 10/44 (2022.01); G06V 10/82 (2022.01); G06V 30/414 (2022.01);
U.S. Cl.
CPC ...
G06N 3/084 (2013.01); G06F 18/214 (2023.01); G06N 5/046 (2013.01); G06T 3/4046 (2013.01); G06T 5/50 (2013.01); G06V 10/454 (2022.01); G06V 10/82 (2022.01); G06V 30/414 (2022.01);
Abstract

Disclosed are methods and systems for detecting screenshot images and protecting against loss of sensitive screenshot-borne data. One disclosed method includes collecting examples of the screenshot images and non-screenshot images and creating labelled ground-truth data for the examples. The method also includes applying re-rendering of at least some of the collected example screenshot images to represent different variations of screenshots that may contain sensitive information, and further includes training a deep learning stack by forward inference and back propagation using labelled ground-truth data for the screenshot images and the examples of the non-screenshot images. The method further includes using results of the back propagation to configure parameters of the trained DL stack for inference from images in production. Also disclosed is applying a screenshot robot to collect the examples of the screenshot images and non-screenshot images.


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