Confidential Data Submission System with Privacy Protection

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Solution Overview

Problem

Users are reluctant to share confidential data, such as salary information, due to privacy concerns about security and misuse, and there are challenges in ensuring the data's confidentiality and accuracy.

Innovation Solution

A system that uses a confidential data frontend to collect and transmit data securely, with encryption and anonymization techniques, including separate encryption keys for user identification and data, timestamp modification, and k-anonymity to protect against inference attacks, ensuring data is used only for specific purposes and maintaining user privacy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If confidential data is collected and stored in a database, then statistical analysis and insights can be provided to users, but user privacy and data security are compromised due to potential misuse or unauthorized access

Engineering Contradiction:

Improveconfidentiality of dataVSAvoidability to provide statistical insights

Core Design Contradiction:

Loss of informationVSProductivity

Solution Approach 1:

The patent segments confidential data into multiple partitions or shards distributed across different storage locations. Each partition contains only a portion of the data, making it impossible to reconstruct individual records without accessing all partitions. This segmentation maintains data confidentiality while still enabling aggregate statistical analysis across all partitions.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediary layer (such as trusted execution environments, homomorphic encryption, or secure multi-party computation protocols) between the data storage and analysis processes. This intermediary enables statistical computations to be performed on encrypted or segmented data without exposing the actual confidential values, thus preserving privacy while providing analytical insights.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Quantity of substance

If users are encouraged to submit confidential data, then more comprehensive statistical analysis becomes possible, but data accuracy and reliability decrease due to spam or over-representation by certain users

Engineering Contradiction:

Improvevolume of confidential dataVSAvoidaccuracy of confidential data

Core Design Contradiction:

Quantity of substanceVSReliability

Solution Approach 1:

The patent implements feedback mechanisms where the system monitors submission patterns, detects anomalies such as spam or over-representation, and adjusts data collection or weighting accordingly. This feedback loop maintains data quality by identifying and correcting unreliable submissions while preserving valuable confidential data from legitimate users.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent changes parameters associated with confidential data submissions, such as assigning weights, timestamps, or verification levels to different data points. By modifying these parameters, the system can distinguish between reliable and unreliable submissions, filter out spam, and ensure that statistical analyses reflect accurate representations of the underlying confidential data.

Inventive Principle:

Principle #35Parameter changes

3Object-affected harmful factors

If confidential data is encrypted and anonymized, then user privacy is protected, but data usability and analytical precision are reduced

Engineering Contradiction:

Improveprivacy risks to usersVSAvoidprecision of statistical analysis

Core Design Contradiction:

Object-affected harmful factorsVSMeasurement precision

Solution Approach 1:

The patent applies preliminary actions by pre-processing confidential data through encryption, segmentation, or anonymization techniques before storage or analysis. This preliminary protection enables subsequent statistical operations to be performed on protected data without compromising privacy, while advanced cryptographic methods preserve sufficient precision for meaningful analysis.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent employs composite approaches combining multiple privacy-preserving techniques (e.g., differential privacy with encrypted computation, or segmented storage with secure query processing). This composite methodology balances privacy protection with analytical precision by layering different protection mechanisms that collectively maintain both confidentiality and data usability.

Inventive Principle:

Principle #40Composite materials

Data Source

PatentUS10158645B1Protecting against spam and over-representation in submission of confidential data

Publication Date: 2018.12.18 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

In an embodiment, a submission history table is maintained by tracking an identification of each user making a submission of a confidential data value and a timestamp of when the corresponding submission was made. A first confidential data value submission is received from a user having a first identification. Member usage information for the user having the first identification, are retrieved based on the first identification. The submission history table is referenced to determine a length of time since the user having the first identification last made a submission of confidential data. It is determined that the user having the first identification is not permitted to submit confidential information based on the member usage information and the length of time since the user having the first identification last made a submission of confidential data. In response to the determining, the first confidential data value is discarded.