Encrypted Data Aggregation for Privacy-Preserving Measurement
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing analytics systems face challenges in aggregating interaction data across multiple entities while maintaining user privacy, as they often require access to personal information to perform aggregation, which compromises user anonymity.
Innovation Solution
A method involving advanced cryptography and computer architectures that encrypt and conceal user identifiers and values, allowing for secure aggregation of data without revealing personal information, using techniques like elliptic curve encryption and homomorphic encryption to enable secure data correlation and credit distribution among content publishers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional analytics systems aggregate interaction data, then measurement precision is improved, but user privacy is compromised due to access to personal information
Solution Approach 1:
The system segments the aggregation process into multiple independent computing systems, each holding different data portions. The first computing system holds encrypted identifiers, the second holds encrypted values, and a third decrypts results. This segmentation allows aggregation to proceed without any single system accessing both identifiers and values in plaintext, thus maintaining privacy while achieving measurement precision.
Solution Approach 2:
The patent introduces encrypted identifiers and encrypted values as intermediary representations that enable aggregation without direct access to personal information. These encrypted forms act as mediators that preserve the ability to perform aggregation operations while preventing privacy compromise, as the encryption schemes allow mathematical operations on encrypted data without decryption.
2Object-affected harmful factors
If encrypted data is used to protect privacy, then user privacy is improved, but device complexity increases due to cryptographic operations
Solution Approach 1:
The patent extracts the cryptographic complexity from the core aggregation logic by separating encryption/decryption operations into dedicated computing systems. The first computing system performs encryption on identifiers, the second system performs aggregation on encrypted values, and the third system handles decryption. This extraction allows each component to be optimized independently, managing overall system complexity while maintaining strong privacy protection.
Solution Approach 2:
The system performs preliminary encryption of identifiers and values before the aggregation process begins. By pre-encrypting the data using established cryptographic schemes, the patent eliminates the need for complex real-time encryption during aggregation, reducing operational complexity while maintaining privacy protection throughout the measurement process.
Data Source
AI summary
A method disclosed herein may include receiving, at a first computing system, encrypted identifiers and encrypted values, performing, by the first computing system, a concealing operation on the encrypted identifiers to produce concealed encrypted identifiers, wherein the concealing operation conceals the encrypted identifiers from the first computing system and a second computing system but enables matching between the concealed encrypted identifiers, decrypting, by the second computing system, the concealed encrypted identifiers to produce concealed identifiers, and performing, by the second computing system, an aggregation operation using the concealed identifiers and the encrypted values to produce an encrypted aggregate value without accessing personally identifiable information associated with the encrypted values.