IP Library Granted Patent US 11,093,645
Granted Patent B2
US 11,093,645 · App. 16/447,061 · Granted Aug 17, 2021

Coordinated de-identification of a dataset across a network

Inventor: Aris Gkoulalas-Divanis (Waltham, MA)
Assignee: International Business Machines Corporation
G06F21/6254G06F21/602G06F21/604
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Quick Facts
Patent No.
US 11,093,645
App. No.
16/447,061
Granted
Aug 17, 2021
Kind
B2
Abstract

Methods, systems, and computer program products are provided. A network device receives, from a client device, a description of a dataset to be de-identified, and a list of one or more data de-identification techniques selected from groups consisting of a group of data masking techniques and a group of data pseudonymization techniques, and their configuration options supported by the client device. A first technique, from the at least one group of techniques and its configuration options supported by the client device and the network device are determined. The network device receives a dataset produced at the client device by applying the first technique and selected configuration options to corresponding attributes from the client device. The network device applies a de-identification technique to the dataset to produce a resulting set of de-identified data, wherein the de-identification technique is coordinated with the first technique and its configuration options to de-identify the dataset.

Claims (19)

1. A method of de-identifying a dataset comprising:

receiving information from a client device at a network device, wherein the information includes a list of at least one group of techniques supported by the client device and selected from groups consisting of a group of data masking techniques and a group of data pseudonymization techniques, configuration options associated with the at least one group of techniques supported by the client device, and a first data dictionary of a dataset to be de-identified, the first data dictionary including attribute names, attribute types and associated metadata including attribute descriptions of attributes of the dataset;

mapping at the network device attributes of the first data dictionary to attributes of a second data dictionary included in the network device by matching attributes of the first data dictionary with attributes of the second data dictionary based on corresponding attribute names and attribute descriptions, the second data dictionary being different from the first data dictionary and including attribute names, attribute types and associated metadata including attribute descriptions of attributes that appear in each ingested data source, the second data dictionary further including a characterization of all direct identifiers from the each ingested data source leading to recognition of direct identifiers of the dataset;

determining at the network device first techniques and associated configuration options mutually supported by the client device and the network device based on the at least one group of techniques, wherein the determined first techniques are compatible with de-identification techniques of the network device and selected from a group of data masking techniques and data pseudonymization techniques;

sending the determined first techniques to the client device;

receiving at the network device the dataset from the client device, wherein the dataset is produced at the client device by applying one or more of the determined first techniques and the associated configuration options to corresponding attributes; and

applying a de-identification technique to the dataset at the network device to produce a resulting set of de-identified data, wherein the de-identification technique is compatible with the applied one or more first techniques and the associated configuration options to de-identify the dataset.

2. The method of claim 1 , wherein the network device resides within a cloud computing environment.

3. The method of claim 1 , wherein the attributes of the first data dictionary include one or more direct identifiers.

4. The method of claim 3 , wherein the applying the de-identification technique further comprises:

identifying one or more sets of quasi-identifiers within the dataset; and

applying the de-identification technique to the identified one or more sets of quasi-identifiers to produce the resulting set of de-identified data.

5. The method of claim 4 , wherein the identifying the one or more sets of quasi-identifiers comprises:

analyzing values of attributes of each record to find unique combinations of the values; and

identifying attributes of the unique combinations of the values as the one or more sets of quasi-identifiers.

6. The method of claim 1 , further comprising:

applying further protection to the resulting set of de-identified data at the network device to improve a privacy level by extending the one or more first techniques applied at the client device using compatible techniques supported at the network device;

identifying at least one sensitive attribute within the dataset; and

applying the de-identification technique to the at least one identified sensitive attribute to produce the resulting set of de-identified data.

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 21, 2024
From: GREEN MARKET SQUARE LIMITED
To: WORKDAY, INC.
Reel/Frame 067801/0892 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 29, 2024
From: GREEN MARKET SQUARE LIMITED
To: WORKDAY, INC.
Reel/Frame 067556/0783 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 27, 2022
From: INTERNATIONAL BUSINESS MACHINES CORPORATION
To: GREEN MARKET SQUARE LIMITED
Reel/Frame 058888/0675 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 20, 2019
From: GKOULALAS-DIVANIS, ARIS
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 049538/0573 →