Confidential Data Encryption with Dual-Key Segmentation
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Solution Overview
Problem
Users are reluctant to share confidential data, such as salary information, due to privacy concerns about data security and usage, making it challenging to collect and maintain accurate and reliable data for statistical analysis.
Innovation Solution
A system that uses a confidential data frontend to collect and encrypt user data, storing it in a backend database with separate encryption keys for identifying and confidential information, ensuring security and anonymization, and only providing insights to users who contribute their own data, using a machine learning algorithm to determine eligibility based on engagement scores.
Engineering Contradictions & Design Principles
Engineering 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 concerns and security risks increase
Solution Approach 1:
The patent segments confidential data into two separate encrypted columns: one for confidential information (encrypted with first key) and one for user identification (encrypted with second key). This segmentation allows the system to maintain data utility for statistical analysis while reducing security risks by preventing unauthorized linkage between user identities and their confidential data.
Solution Approach 2:
The patent introduces an encrypted transaction number as an intermediary element that links confidential data submissions to user accounts without exposing either the confidential information or user identity. This intermediary enables the system to track data contributions and provide insights to eligible users while maintaining privacy and security.
2Reliability
If users are encouraged to share confidential data, then data accuracy and reliability improve, but user reluctance due to privacy concerns increases
Solution Approach 1:
The patent implements a feedback mechanism where users who submit confidential data receive personalized insights and rankings based on their data contributions. This feedback loop incentivizes users to share accurate and reliable confidential information by demonstrating tangible benefits from their participation.
Solution Approach 2:
The patent performs preliminary encryption of confidential data and user identification before storage, and pre-establishes the security framework and privacy protections. This preliminary action builds user trust before data collection begins, encouraging greater participation and data accuracy.
3Object-affected harmful factors
If separate encryption keys are used for identifying and confidential information, then data security is enhanced, but system complexity increases
Solution Approach 1:
The patent segments the encryption key management system into distinct key pairs: one for encrypting confidential information and another for encrypting user identification. This segmentation enhances security by ensuring that compromise of one key does not expose the other, while the modular structure manages complexity through clear separation of concerns.
Data Source
AI summary
In an example embodiment, a submission of confidential data is received from a user. Then, the confidential data is encrypted using a first public key generated as part of a first public key-first private key pair. The encrypted confidential data is stored in a first column of a first submission table in a confidential information database. An identification of the user is encrypted using a second public key different than the first public key, the second public key generated as part of a first public key-first private key pair. Then, the encrypted identification of the user is stored in a second submission table in the confidential information database. The first private key is provided to a first component to decrypt the confidential information, without providing the second private key to the first component.