Post-quantum Private Stream Aggregation via LWE Cryptography
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing private stream aggregation systems face limitations in performance due to discrete logarithm computation and are vulnerable to future quantum computer attacks, compromising data privacy and security.
Innovation Solution
The implementation of a Learning with Errors (LWE) cryptographic system with additive homomorphic properties, allowing clients to transmit encrypted data with error vectors that preserve differential privacy, even to untrusted aggregators, using a modified LWE key generation process that resists both classical and quantum computational attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If discrete logarithm computation is used for homomorphic encryption in PSA systems, then differential privacy is preserved, but data transmission efficiency is limited and performance is compromised
Solution Approach 1:
The patent changes the cryptographic parameter basis from discrete logarithm problems to lattice-based problems (Learning With Errors - LWE). This parameter change enables homomorphic operations on encrypted data without requiring computationally intensive discrete logarithm computations, thereby improving data transmission efficiency while maintaining the security and differential privacy guarantees needed for PSA systems
2Reliability
If discrete logarithm-based cryptography is used in PSA systems, then current security requirements are met, but vulnerability to quantum computer attacks increases
Solution Approach 1:
The patent transitions from discrete logarithm-based cryptographic parameters to lattice-based cryptographic parameters (specifically the Learning With Errors problem). Lattice-based cryptography is recognized as a post-quantum cryptographic approach that remains secure against quantum computer attacks, thereby eliminating the vulnerability to quantum computation while maintaining current security protection levels
Solution Approach 2:
The patent converts the potential harm of quantum computer vulnerability into a benefit by adopting quantum-resistant cryptography. The Learning With Errors problem provides security that is believed to be hard for both classical and quantum computers, turning the threat of quantum advancement into an opportunity to strengthen long-term security posture
3Reliability
If clients transmit only single bit information in encrypted form, then differential privacy is maintained, but information transmission capacity is reduced
Solution Approach 1:
The patent changes the homomorphic encryption scheme to operate on larger algebraic structures (lattice-based homomorphic encryption) that can accommodate multi-bit or even multi-integer values in each encrypted message. This allows clients to transmit more information per message while the lattice-based cryptography maintains the differential privacy guarantees through controlled noise addition during homomorphic operations
Data Source
AI summary
A method for operating an aggregator in a private stream aggregation (PSA) system has been developed. The method includes receiving a plurality of encrypted messages from a plurality of clients, each encrypted message corresponding to a vector in a learning with errors (LWE) public key, adding, the plurality of encrypted messages to generate an aggregate data set, extracting a summation of a plurality of error vectors in the plurality of encrypted messages from the aggregate data set, decrypting the summation of the encrypted data contained in the plurality of encrypted messages using a private key stored in the memory of the aggregator to generate a plaintext sum of noisy data generated by the plurality of clients, and generating, with the processor, an output of the plaintext sum of noisy data that preserves differential privacy of each client in the plurality of clients.