Homomorphic Encryption Masking via Null Space
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Solution Overview
Problem
Existing cryptographic systems are vulnerable to side-channel attacks, particularly during homomorphic encryption, as secret data becomes exposed when multiplied by varying ciphertexts, leading to increased latency and resource consumption due to the need for additional unmasking operations in masking techniques.
Innovation Solution
Implementing masking techniques that generate masks from the null space of secret data, allowing for secure operations without separate computations on masked data and masks, and eliminating the need for additional unmasking operations, ensuring that masks are nullified during decryption without affecting the final output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If masking techniques are implemented to protect against side-channel attacks, then security is improved, but additional unmasking operations are required which increase latency and resource consumption
Solution Approach 1:
The harmful unmasking operations are extracted and eliminated from the decryption process. The patent achieves this by using masks from the null space of the secret data, which are automatically nullified during decryption without requiring separate unmasking steps, thus removing the time-consuming operations while maintaining security
Solution Approach 2:
The patent changes the parameter of the mask by selecting it from the null space of the secret data (s^T M = 0) rather than using conventional masks. This parameter change ensures the mask is automatically nullified during decryption, eliminating the need for additional unmasking operations and reducing latency
2Reliability
If masking techniques are implemented to protect against side-channel attacks, then security is improved, but resource consumption increases due to additional unmasking operations
Solution Approach 1:
The harmful unmasking operations are extracted and eliminated from the decryption process. The patent achieves this by using masks from the null space of the secret data, which are automatically nullified during decryption without requiring separate unmasking steps, thus removing the resource-consuming operations while maintaining security
Solution Approach 2:
The mask serves itself by being automatically nullified during the decryption process through the mathematical property s^T M = 0. This self-service mechanism eliminates the need for additional unmasking operations, reducing computational resource consumption while maintaining security
3Reliability
If conventional masking techniques are used with separate computations on masked data and masks, then security is improved, but device complexity increases
Solution Approach 1:
The patent merges the masking and decryption operations into a single unified process. By using masks from the null space of the secret data, the decryption operation automatically handles mask nullification, eliminating the need for separate unmasking computations and reducing overall device complexity
Solution Approach 2:
The mask from the null space serves multiple functions simultaneously: it provides security against side-channel attacks and automatically nullifies itself during decryption. This multi-functionality eliminates the need for separate unmasking operations, reducing computational complexity while maintaining security
Data Source
AI summary
Aspects and implementations are directed to systems and techniques for protecting cryptographic operations against side-channel attacks by masking a ciphertext data using one or more masks randomly sampled from a null space associated with a tensor representation of a secret data and generating a plaintext data using the masked ciphertext data.