Homomorphic Encryption for Privacy-Preserving Data Utility
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Solution Overview
Problem
The challenge lies in balancing data utility for insights and efficiency with the need for strict data privacy and regulatory compliance, particularly in sharing personal data that carries risks of identity disclosure and unwarranted persecution.
Innovation Solution
The implementation of homomorphic encryption cryptography allows for secure, privacy-preserving computations by encrypting data at the agent level, enabling sharing and centralized computation without exposing personal identifiable information, using a homomorphic public key for encryption and a private key for decryption, and employing random identifiers for anonymization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If personal data is shared and centralized for analysis, then data utility and insights are improved, but data privacy and security are compromised
Solution Approach 1:
Data is encrypted with homomorphic encryption before being shared and centralized for analysis. This preliminary encryption action ensures that data remains protected throughout the entire processing pipeline, allowing utilities to be extracted without ever exposing the underlying personal information.
Solution Approach 2:
Homomorphic encryption acts as an intermediary mechanism that enables centralized data processing while maintaining privacy. The encryption scheme allows computations to be performed on encrypted data, serving as a mediator between the need for data analysis and the requirement for data protection.
2Reliability
If data is encrypted to protect privacy, then security is improved, but computational efficiency and data processing speed deteriorate
Solution Approach 1:
The patent employs homomorphic encryption schemes that have been optimized for specific computational operations. By changing the cryptographic parameters and selecting appropriate homomorphic encryption variants, the system achieves a balance between security and computational efficiency for the specific use case of extracting data utilities.
Data Source
AI summary
It is provided an apparatus comprising interface circuitry, machine-readable instructions, and processing circuitry to execute the machine-readable instructions. The machine-readable instructions comprise instructions to encrypt data of a first agent with a homomorphic public key. The first agent is connected to a network. The machine-readable instructions further comprise instructions to transmit the encrypted data of the first agent and the homomorphic public key to a server and to request data from the server, the requested data comprising a reference value for the data of the first agent. The reference value is based on the data of the first agent and on the data of one or more second agents, the one or more second agents are connected to the network. The machine-readable instructions further comprise instructions to receive the requested data from the server. The requested data is encrypted with the homomorphic public key.