US 2026/0089140 A1 · REDACTION OF DIGITAL DOCUMENTS UTILIZING MAXIMUM LIKELIHOOD GAUSSIAN NOISE ADDITION AND PROCESS OF REVERSE ESTIMATION

Abstract

This disclosure relates to protecting sensitive information in electronic images of documents by removing or obscuring the sensitive information in a reversible manner. A system and process may receive a digital image, identify the sensitive information in the image, and add Gaussian noise to a document in a unique way that obscures the sensitive information. For security, the computing platform ensures that noisy data added to a document is distinct from noise patterns that have been added to other digital files. Further aspects include a system and process for reverse estimation to restore a document with added noise to its original form. The addition and removal of noise may be based on maximum likelihood estimation and may utilize models trained on prior sets of noisy data to determine uniqueness of the noisy data.

Claims20

Dependent claims

A computing platform, comprising:

at least one processor;
a communication interface communicatively coupled to the at least one processor and a memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:
receive a digital image;
identify a starting point in the digital image where noise may be added;
generate a starting noise variance corresponding to the starting point;
identify, using maximum likelihood estimation, a new noisy data set estimated to be unique, wherein the new noisy data set comprises a plurality of additional points in the digital image and a plurality of additional noise variances corresponding to the plurality of additional points, respectively, wherein the plurality of additional points are ordered in a sequence relative to the starting point;
add the new noisy data set to the digital image to generate a Gaussian noisy image;
and
transmit the Gaussian noisy image via an unsecured network.

6 more elements

One or more non-transitory computer-readable media storing instructions that, when executed by a computing platform comprising at least one processor, memory, and a communication interface, cause the computing platform to:

receive a digital image;
detect one or more regions in the digital image comprising sensitive data;
and
identify a starting point in the one or more regions where noise may be added;
generate a starting noise variance corresponding to the starting point;
identify, using maximum likelihood estimation, a new noisy data set estimated to be unique, wherein the new noisy data set comprises a plurality of additional points in the one or more regions and a plurality of additional noise variances corresponding to the plurality of additional points, respectively, wherein the plurality of additional points are ordered in a sequence relative to the starting point, and wherein the plurality of additional noise variances has a Gaussian distribution;
add the new noisy data set to the digital image to generate a Gaussian noisy image;
and
transmit the Gaussian noisy image via an unsecured network.

6 more elements

Dependencies are inferred from the claim text.

Redaction of digital documents utilizing maximum likelihood gaussian noise addition and process of reverse estimation

Life of this patent

Redaction of digital documents utilizing maximum likelihood gaussian noise addition and process of reverse estimation

Life of this patent

Abstract

Claims20