Homomorphic Encryption Randomization for Side-Channel Security
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current homomorphic encryption systems are impractical for widespread use in cloud computing due to limitations in performing computations on encrypted data without decryption, making them vulnerable to security breaches and inefficient for secure data processing.
Innovation Solution
A fully homomorphic encryption method is developed using matrix-based and polynomial-based randomizing and homomorphic transformation functions, allowing secure computations over a commutative ring, specifically designed for crypto applications, which includes randomizing and encrypting data in a way that protects against side-channel attacks and provides fault detection and verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If homomorphic encryption is implemented to enable secure cloud computing, then data security is improved, but computational efficiency deteriorates
Solution Approach 1:
The patent segments homomorphic encryption into two distinct modes: randomized homomorphic mode for security-critical operations and deterministic homomorphic mode for efficiency-critical operations. This segmentation allows the system to optimize for either security or efficiency depending on the specific computational context, resolving the contradiction between data security and computational efficiency.
Solution Approach 2:
The system dynamically switches between randomized and deterministic homomorphic modes based on the computational requirements of different operations. Randomized mode is used when security is paramount, while deterministic mode is used when efficiency is critical, allowing the system to adapt its security-efficiency tradeoff in real-time.
2Reliability
If randomized homomorphic mode is used to enhance security, then resistance to side-channel attacks is improved, but computational overhead increases
Solution Approach 1:
The patent applies randomized homomorphic mode selectively to specific operations where side-channel attack resistance is most critical, rather than uniformly across all computations. This localized application of randomization provides targeted security enhancement while minimizing the overall computational overhead associated with randomized operations.
3Productivity
If deterministic homomorphic mode is used to improve efficiency, then computational speed is improved, but security against certain attacks deteriorates
Solution Approach 1:
The system changes the security parameter of the homomorphic mode based on the computational context. Deterministic mode uses simplified parameters for efficiency, while randomized mode uses more robust parameters for security. This parameter adjustment allows the system to optimize performance while maintaining adequate security through selective mode switching.
Data Source
AI summary
In one embodiment, a method for reducing information leakage in order to counter side channel attacks against a secure execution environment is described, the method including receiving at the secure execution environment a first input comprising a key comprising a sequence of k input elements in a commutative ring, CR, receiving at the secure execution environment a second input comprising a text comprising a sequence of p input elements in the commutative ring, CR, defining an input INP comprising a sequence of j input elements, wherein INP comprises either one or both of the first input or the second input, performing one of a matrix randomization operation or a polynomial randomization operation on the inputs, and producing a randomized output.