Encrypted Data Structures for Private Reach and Frequency Computation
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Solution Overview
Problem
Computing the union, intersection, or frequency of large sets of data distributed across multiple sources involves sharing private or protected information, which negatively impacts privacy and security, and existing methods face scalability and computational resource exhaustion issues.
Innovation Solution
A method and system for detecting collisions in encrypted data structures using zero-knowledge cryptographic computation, employing additively homomorphic encryption and probabilistic data structures like bloom filters to combine encrypted data structures without decrypting, enabling parallelizable deduplication and frequency estimation across multiple data providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is shared between multiple sources to compute union, intersection, or frequency, then computational analysis can be performed, but privacy and security are negatively impacted
Solution Approach 1:
The patent introduces an intermediary encryption layer that allows data to be processed without being decrypted. Encrypted data structures are combined through homomorphic operations, enabling frequency and reach computation while maintaining privacy. The encryption scheme acts as a mediator between data sources and the computation system, preventing direct exposure of sensitive information.
Solution Approach 2:
The patent replaces traditional mechanical data sharing and processing mechanisms with cryptographic homomorphic operations. Instead of decrypting and processing data traditionally, the system uses homomorphic encryption to perform computations directly on encrypted data, substituting conventional data processing mechanics with cryptographic operations that preserve privacy.
2Measurement precision
If large sets of data are processed to determine intersection or union, then comprehensive analysis is achieved, but computational resources are exhausted
Solution Approach 1:
The patent segments large datasets into encrypted data structures that can be processed in parallel. By dividing the computation into independent operations on encrypted structures, the system achieves comprehensive analysis without requiring proportional increases in computational resources. The segmentation allows distributed processing that maintains precision while reducing resource consumption.
Solution Approach 2:
The patent changes the fundamental parameters of data processing by operating on encrypted representations rather than plain data. This parameter change enables frequency and reach calculations to be performed with significantly reduced computational overhead, as the homomorphic operations on encrypted data structures are more efficient than traditional data processing approaches.
3Object-affected harmful factors
If encrypted data structures are combined without decryption, then privacy is maintained, but collision detection becomes challenging
Solution Approach 1:
The patent introduces validity bits as an intermediary mechanism that facilitates collision detection in encrypted data structures. These validity bits act as markers that indicate whether collisions have occurred during the combination process, enabling the system to detect and handle collisions without decrypting the underlying data. This intermediary approach maintains privacy while solving the detection challenge.
Data Source
AI summary
Systems and methods for detecting a collision when combining a first encrypted data structure and a second encrypted data structure are disclosed. The system can receive the first encrypted data structure representative of a first plurality of registers. Each register in the first plurality of registers can have an encrypted fingerprint value, and an encrypted register identifier value. The system can receive the second encrypted data structure representative of a second plurality of registers. The system can calculate a first sum associated with a first register of the first plurality of registers based on the fingerprint value of the first register. The system can calculate a second sum associated with a second register of the second plurality of registers. The system can determine a validity bit associated with the collision based on a comparison of the first sum and the second sum.