US 10,949,961 B1 · Detecting screenshot images for protecting against loss of sensitive screenshot-borne data

Abstract

Disclosed is detecting screenshot images and protecting against loss of sensitive screenshot image data. The method collects examples of screenshot images and non-screenshot images, creates labelled ground-truth data for the examples, and applies re-rendering of collected images to represent variations that may contain sensitive information. The method includes training a DL stack by forward inference and back propagation using labelled ground truth data for the screenshots, storing parameters of the trained DL stack for inference from production images, and using a production DL stack with the stored parameters to classify at least one production image by inference as containing a screenshot image. Further, DL stack includes a first set of layers closer to an input layer being pre-trained to perform image recognition before exposing a second set of layers further from the input layer of DL stack to the labelled ground truth data for the screenshot images and non-screenshot images.

Claims20

Dependent claims

A method of detecting screenshot images and protecting against loss of sensitive screenshot-borne data, including:

collecting examples of the screenshot images and non-screenshot images and creating labelled ground-truth data for the examples;
applying re-rendering of at least some of the collected example screenshot images to represent different variations of screenshots that may contain sensitive information;
training a deep learning (abbreviated DL) stack by forward inference and back propagation using labelled ground-truth data for the screenshot images and the examples of the non-screenshot images;
storing parameters of the trained DL stack for inference from images in production, following training;
and
using a production DL stack with the stored parameters to classify at least one production image by inference as containing a screenshot image.

3 more elements

A tangible non-transitory computer readable storage media, including program instructions loaded into memory that, when executed on processors, cause the processors to implement a method of detecting screenshot images and protecting against loss of at least one image-borne screenshot, the method including:

collecting examples of the screenshot images and non-screenshot images and creating labelled ground-truth data for the examples;
applying re-rendering of at least some of the collected example screenshot images to represent different variations of screenshots that may contain sensitive information;
training a deep learning (abbreviated DL) stack by forward inference and back propagation using labelled ground truth data for the screenshot images and the examples of the non-screenshot images;
storing parameters of the trained DL stack for inference from images in production, following training;
and
using a production DL stack with the stored parameters to classify at least one production image by inference as containing an image-borne screenshot.

3 more elements

Dependencies are inferred from the claim text.

Detecting screenshot images for protecting against loss of sensitive screenshot-borne data

Life of this patent

Detecting screenshot images for protecting against loss of sensitive screenshot-borne data

Life of this patent

Abstract

Claims20