Restricting sensitive query results in information management platforms

• US 9,959,285 B2
• Filed: 08/08/2014
• Issued: 05/01/2018
• Est. Priority Date: 08/08/2014
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Gkoulalas-Divanis, Aris, Wurst, Michael
• Primary Examiner(s): Pham, Tuan A
• Application Number:
  US14/454,808
• Publication Number:
  US 20160042009A1
• Time in Patent Office: 1,362 Days
• Field of Search: None
• CPC Class Codes: G06F 16/176 Support for shared access to files; File sharing support
• CPC Class Codes: G06F 16/242 Query formulation
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 21/6218 to a system of files or objects, e.g. local or distributed file system or database
• CPC Class Codes: G06F 21/6245 Protecting personal data, e.g. for financial or medical purposes
• CPC Class Codes: H04L 63/105 Multiple levels of security

Abstract

As information becomes more accessible to the public, the ability to predict and estimate sensitive data from the data already available to the general public becomes easier. The existing privacy-preserving data mining approaches only consider the information the user is querying and do not consider the information the user already has, and how the user can use that information in combination with the query information to create sensitive data that the user should not have access to. Some embodiments of the present invention provide a query analysis (QA) program that solves the aforementioned problem by taking into account data that a user may already have, whether it is private data or data that is available to the public, and then using that data, along with the data that would be returned in the query, to determine if sensitive data could be recreated.

Claims

1. A method for controlling access to a dataset, the method comprising:

receiving, by one or more computer hardware processors, a request for a first dataset from a user, wherein the first dataset includes one or more first dataset values;

creating, by one or more computer hardware processors, a forecasting model using regression analysis from the first dataset and a second dataset, wherein the second dataset includes one or more second dataset values, and wherein each second dataset value of the one or more second dataset values corresponds to each first dataset value of the one or more first dataset values;

generating, by one or more computer hardware processors, a forecasted dataset using the forecasting model, wherein the forecasted dataset includes one or more forecasted dataset values, and wherein each forecasted dataset value of the one or more forecasted dataset values is forecasted using each corresponding first dataset value and second dataset value;

determining, by one or more computer hardware processors, a difference between values in a third dataset and values in the forecasted dataset for each corresponding third dataset value and forecasted dataset value, wherein the third dataset includes one or more third dataset values, and wherein each third dataset value of the one or more third dataset values corresponds to a forecasted dataset value of the one or more forecasted dataset values; and

comparing, by one or more computer hardware processors, the average of the absolute value of all of the difference to a pre-determined inference condition;

wherein;

the first dataset contains a user-requested dataset; and

the second dataset contains a user-known dataset.

2. The method of claim 1, wherein:

the first dataset is assigned a first access level; and

the third dataset is assigned a second access level, the second access level indicating sensitive data with respect to the first access level.

3. The method of claim 1, further comprising:

responsive to the average of the absolute value of all of the difference meeting the pre-determined inference condition, denying, by one or more computer hardware processors, the request for the first dataset.

4. The method of claim 1, wherein the second dataset includes public data identified in a web crawling process.

5. The method of claim 1, further comprising:

responsive to the average of the absolute value of all of the difference not meeting the pre-determined inference condition, providing, by one or more, the request for the first dataset to the user.