Data processing systems for generating and populating a data inventory

• US 10,282,370 B1
• Filed: 12/19/2018
• Issued: 05/07/2019
• Est. Priority Date: 06/10/2016
• Status: Active Grant

• Current Assignee: OneTrust LLC
• Original Assignee: OneTrust LLC
• Inventors: Barday, Kabir A., Karanjkar, Mihir S., Finch, Steven W., Browne, Ken A., Heard, Nathan W., Patel, Aakash H., Sabourin, Jason L., Daniel, Richard L., Patton-Kuhl, Dylan D., Brannon, Jonathan Blake
• Primary Examiner(s): Deng, Anna C
• Application Number:
  US16/226,272
• Publication Number:
  US 20190129902A1
• Time in Patent Office: 139 Days
• Field of Search: 717101
• CPC Class Codes: G06F 15/76 Architectures of general purpose stored program computers with program plugboard G06F15/08; multicomputers G06F15/16
• CPC Class Codes: G06F 16/254 Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• CPC Class Codes: G06F 16/288 Entity relationship models
• CPC Class Codes: G06F 21/552 involving long-term monitoring or reporting
• CPC Class Codes: G06F 40/186 Templates
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: H04L 63/04 for providing a confidential data exchange among entities communicating through data packet networks
• CPC Class Codes: H04L 63/101 Access control lists [ACL]
• CPC Class Codes: H04L 63/20 for managing network security; network security policies in general filtering policies H04L63/0227
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04W 12/02 Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]

Abstract

In particular embodiments, a data processing data inventory generation system is configured to: (1) generate a data model (e.g., a data inventory) for one or more data assets utilized by a particular organization; (2) generate a respective data inventory for each of the one or more data assets; and (3) map one or more relationships between one or more aspects of the data inventory, the one or more data assets, etc. within the data model. In particular embodiments, a data asset (e.g., data system, software application, etc.) may include, for example, any entity that collects, processes, contains, and/or transfers personal data (e.g., such as a software application, “internet of things” computerized device, database, website, data-center, server, etc.). For example, a first data asset may include any software or device (e.g., server or servers) utilized by a particular entity for such data collection, processing, transfer, storage, etc.

Claims

1. A computer-implemented data processing method of feeding a data inventory with one or more data attribute values, the method comprising:

generating, by one or more processors, a data inventory for one or more data assets used in the collection or storage of personal data

storing, by the one or more processors, the data inventory in computer memory;

modifying, by the one or more processors, the data inventory to include one or more data fields that each define a respective data inventory attribute of a plurality of data inventory attributes;

determining, by the one or more processors, which of the one or more data fields of the data inventory are unpopulated data fields;

determining, by the one or more processors, a respective data inventory attribute value for each of the unpopulated data fields, wherein determining the respective data inventory attribute value for each of the unpopulated data fields comprises;

providing a software application for installation on a computing device that is networked with one or more data repositories associated with an organization, and

providing a communication channel between one or more remote scanning servers and the software application, wherein;

the software application is configured to communicate with the one or more remote scanning servers, and

the software application is configured to scan the one or more data repositories to identify each respective data inventory attribute value from data stored in the one or more data repositories and to transmit each identified respective data inventory attribute value to the one or more remote scanning servers via the communication channel;

in response to determining the respective data inventory attribute value for each of the unpopulated data fields, modifying each of the unpopulated data fields to include the respective data inventory attribute value; and

storing the modified data inventory in the computer memory.

2. The computer-implemented data processing method of claim 1, further comprising:

using an application programming interface to access a third-party information technology system;

receiving one or more pieces of data from the third-party information technology system; and

filling, by one or more processors, the unpopulated data fields based at least in part on the one or more pieces of data.

3. The computer-implemented data processing method of claim 1, the method further comprising:

scanning one or more data repositories on one or more remote computing devices to identify one or more data attributes; and

identifying each respective data inventory attribute value for each of the unpopulated data fields from the one or more data attributes.

4. The computer-implemented data processing method of claim 3, the method further comprising:

analyzing the one or more data attributes and correlating metadata for the scanned one or more data repositories with particular attributes of the one or more data attributes discovered in the one or more data repositories; and

using one or more machine learning techniques to categorize the one or more data attributes based at least in part on a confidence score.

5. The computer-implemented data processing method of claim 4, the method further comprising:

receiving input from a user confirming or denying a categorization of the one or more data elements; and

in response to receiving the input, modifying the confidence score.

6. The computer-implemented data processing method of claim 5, wherein identifying each respective data inventory attribute value for each of the unpopulated data fields from the one or more data attributes comprises identifying each respective data inventory attribute value for each of the unpopulated data fields based on the confidence score.

7. The computer-implemented data processing method of claim 1, wherein generating the data inventory for the one or more data assets used in the collection or storage of personal data comprises generating the data inventory for a plurality of inter-related data assets utilized in the processing of one or more pieces of personal data, and further comprises:

identifying, by one or more processors, from the plurality of inter-related data assets, a storage asset, the storage asset storing the one or more pieces of personal data collected from one or more data subjects;

identifying, by one or more processors, from the plurality of inter-related data assets, a collection asset that transfers the one or more pieces of personal data to the storage asset;

identifying, by one or more processors, from the plurality of inter-related data assets, a transfer asset to which the storage asset transfers the one or more pieces personal data;

digitally storing, by one or more processors, in computer memory, one or more storage asset inventory attributes comprising a type of personal data stored by the storage asset;

digitally storing, by one or more processors, in computer memory, one or more collection asset inventory attributes comprising the one or more pieces of personal data that the collection asset transfers to the storage asset;

digitally storing, by one or more processors, in computer memory, one or more transfer asset inventory attributes comprising the one or more pieces of personal data that the storage asset transfers to the transfer asset; and

generating the data inventory by;

associating the storage asset with the one or more storage asset inventory attributes in computer memory;

associating the collection asset with the one or more collection asset inventory attributes in computer memory;

associating the transfer asset with the one or more transfer asset inventory attributes in computer memory;

electronically linking the collection asset to the storage asset in computer memory;

electronically linking the storage asset to the transfer asset; and

electronically mapping the one or more pieces of personal data to the collection asset, the storage asset, and the transfer asset.

8. The computer-implemented data processing method of claim 7, wherein determining the respective data inventory attribute value for each of the unpopulated data fields comprises determining at least one data inventory attribute selected from a group consisting of:

the one or more storage asset inventory attributes;

the one or more collection asset inventory attributes; and

the one or more transfer asset inventory attributes.

10. The computer-implemented data processing method of claim 1, wherein determining the respective data inventory attribute value for each of the unpopulated data fields comprises determining, by the one or more remote scanning servers, for each of the respective data inventory attribute values, that the respective data inventory attribute value is the value that should be used to populate its respective unpopulated data field.

9. A data processing data inventory population system comprising:

one or more processors;

computer memory; and

a computer-readable medium storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising;

accessing a plurality of data assets of a data model used in the collection or storage of personal data, the data model defining one or more electronic links between the plurality of data assets and storing a plurality of data inventories that define a plurality of inventory attributes for each of the plurality of data assets;

identifying a first data inventory from the plurality of data inventories, each of the plurality of data inventories being associated with a respective data asset, wherein the first data inventory comprises a plurality of fields that each define a respective inventory attribute of a first data asset associated with the first data inventory;

determining, for each respective one of the plurality of fields of the first data inventory, whether the respective field is a populated inventory attribute field containing an attribute value for one of the plurality of inventory attributes, or an unpopulated inventory attribute field not containing an attribute value for one of the plurality of inventory attributes;

determining, for each respective one of the one or more unpopulated inventory attributes fields, one or more attribute values for use in populating the respective unpopulated inventory attribute field, wherein the one or more attribute values comprise a second data asset that is not included in the plurality of data assets of the data model;

in response to determining the one or more attribute values for each of the one or more unpopulated inventory attribute fields, the one or more processors performing operations comprising;

generating a second data inventory for the second data asset, the second data inventory storing one or more second data asset inventory attributes comprising the first data asset, and a type of personal data collected or stored by the second data asset,

modifying the data model to include the second data asset and the second data inventory, and

linking the first data asset to the second data asset in the data model;

modifying the first data inventory to include the one or more attribute values for each of the one or more unpopulated inventory attributes fields by populating each of the plurality of unpopulated inventory attribute fields with a respective one of the determined attribute values; and

storing the modified first data inventory in computer memory.

11. The data processing data inventory population system of claim 9, wherein the system is further configured for, in response to determining the one or more attribute values for each of the one or more unpopulated inventory attribute fields, digitally storing, by the one or more processors, the modified data model in computer memory.

12. The data processing data inventory population system of claim 9, wherein determining the one or more attribute values comprises determining the one or more attribute values using one or more intelligent identity scanning means.

13. The data processing data inventory population system of claim 9, wherein:

the computer-readable medium further stores computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising;

using an application programming interface to access a third-party information technology system; and

integrating the data processing data inventory population system with the third-party information technology system via the application programming interface; and

determining the one or more attribute values comprises determining the one or more attribute values by retrieving the one or more attribute values from the third-party information technology system.

14. The data processing data inventory population system of claim 9, wherein the computer-readable medium further stores computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

scanning one or more data repositories to identify one or more data attributes;

analyzing the one or more data attributes and correlating metadata for the scanned one or more data repositories with particular attributes of the one or more data attributes discovered in the one or more data repositories; and

determining the one or more attribute values based on the one or more data elements.

15. The data processing data inventory population system of claim 14, wherein analyzing the one or more data attributes and correlating metadata for the scanned one or more data repositories with the particular attributes of the one or more data attributes discovered in the one or more data repositories comprises retrieving schema details for each of the one or more data attributes from the scanned one or more data repositories.

16. The data processing data inventory population system of claim 15, wherein the schema details comprise one or more schema details selected from a group consisting of:

an asset ID;

a Schema ID; and

a connection string.

17. The data processing data inventory population system of claim 15, wherein the computer-readable medium further stores computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising analyzing the one or more data repositories to determine whether each particular data repository is part of an existing data model of data assets.

18. The data processing data inventory population system of claim 9, wherein each populated inventory attribute field comprises one or more known attributes.

19. The data processing data inventory population system of claim 9, wherein the computer-readable medium further stores computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising analyzing the one or more data repositories to determine whether each particular data repository is part of an existing data model of data assets.

20. The data processing data inventory population system of claim 9, wherein determining the one or more attribute values comprises determining the one or more attribute values using a combination of an application programming interface and a data repository scanning system.