Homomorphic Encryption for Secure Distributed Ledger Computations
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Solution Overview
Problem
Existing information handling systems face challenges in securely processing data using third-party computing resources due to exposure of sensitive data, limited resources in centralized services, security concerns, and reliance on centralized providers, which can lead to data breaches and service disruptions.
Innovation Solution
A decentralized system utilizing a secure distributed transaction ledger and homomorphic encryption to facilitate computations without exposing input or output data, allowing secure and automatic processing by third parties while maintaining data confidentiality and integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a centralized service is used to provide computational resources, then resource availability is improved, but security and data exposure risks worsen
Solution Approach 1:
The system segments computational resources into distributed nodes across a peer-to-peer network rather than consolidating them in a single centralized service. This segmentation allows multiple third parties to contribute computing power while maintaining security through decentralization, resolving the contradiction between resource availability and data exposure risk.
Solution Approach 2:
Homomorphic encryption acts as an intermediary mechanism that enables computations on encrypted data without exposing the plaintext. Third-party computational nodes can process encrypted inputs and generate encrypted outputs, allowing resource utilization while maintaining data confidentiality throughout the computation process.
2Productivity
If third parties are used to perform computations, then resource utilization is improved, but data security and trust issues worsen
Solution Approach 1:
Homomorphic encryption serves as a trusted intermediary that eliminates the need to trust third-party computational nodes with plaintext data. The encryption scheme ensures that nodes can perform computations reliably on encrypted data without being able to access or misuse the underlying sensitive information, thus maintaining both productivity and reliability.
Solution Approach 2:
The system replaces the mechanical trust relationship (relying on third parties to securely handle data) with a cryptographic mechanism (homomorphic encryption). This substitution allows computations to be performed by untrusted third parties while mathematically guaranteeing data security, resolving the contradiction between utilizing external resources and maintaining reliability.
3Ease of operation
If centralized services are used for data processing, then ease of operation is improved, but system reliability and resistance to attacks worsen
Solution Approach 1:
The centralized service model is segmented into a distributed peer-to-peer network of computational nodes. This segmentation improves reliability by eliminating single points of failure - if some nodes go offline or are attacked, the system continues to operate using remaining nodes, while maintaining ease of operation through a unified interface for submitting and retrieving computational tasks.
Data Source
AI summary
Aspects of the present invention provide systems and methods that facilitate computations that are publically defined while assuring the confidentiality of the input data provided, the generated output data, or both using homomorphic encryption on the contents of the secure distributed transaction ledger. Full homomorphic encryption schemes protect data while still enabling programs to accept it as input. In embodiments, using a homomorphic encryption data input into a secure distributed transaction ledger allows a consumer to employ highly motivated entities with excess compute capability to perform calculations on the consumer's behalf while assuring data confidentiality, correctness, and integrity as it propagates through the network.