Secure Multi-Party Exact Homomorphic Encryption for Scalable Computation
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Solution Overview
Problem
Existing homomorphic encryption technologies face scalability issues due to noise accumulation and the need for extensive quantum operations, limiting their practical application in secure data processing and quantum computing environments.
Innovation Solution
A system and method for secure multi-party exact homomorphic encryption (SMPEHE) involving a key generation module, message encryption module, and computation module, utilizing multivariate polynomial sets and elementary gates to encrypt and compute on encrypted data without decryption, ensuring fault-tolerant quantum computations and hyper quantum resilience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional homomorphic encryption is used to perform encrypted computations, then data security is improved, but noise accumulates exponentially with the number of multiplications, limiting computation depth
Solution Approach 1:
The patent introduces a trusted third party (TTP) as an intermediary that generates and distributes secret keys to multiple parties. This TTP-mediated key distribution system enables secure multi-party computation by allowing parties to perform homomorphic operations on encrypted data without directly sharing their private keys, thus maintaining security while enabling deeper computations through proper key management and noise control mechanisms.
Solution Approach 2:
The patent segments the computation process into multiple controlled stages with intermediate verification points. By dividing the homomorphic computation into discrete steps where noise can be managed and controlled at each stage, the system prevents exponential noise accumulation. The segmentation also allows for intermediate decryption and re-encryption operations under controlled conditions, maintaining accuracy while enabling complex computations.
2Reliability
If quantum operations are used to achieve post-quantum security, then cryptographic strength is improved, but the number of physical qubits required exceeds available quantum computing resources
Solution Approach 1:
The patent uses classical computational resources to simulate and verify quantum cryptographic protocols. Instead of requiring actual quantum hardware for every operation, the system employs classical algorithms that replicate quantum computational effects, thereby achieving post-quantum security levels with available classical computing resources. This copying approach allows the system to maintain quantum-resistant security without needing excessive physical qubits.
Solution Approach 2:
The patent replaces physical quantum mechanical systems with classical computational mechanisms. By substituting actual quantum operations with classically simulatable algorithms that produce equivalent cryptographic results, the system achieves post-quantum security without requiring large-scale quantum hardware. This substitution enables the use of standard computational resources while maintaining security against quantum attacks.
3Reliability
If fault-tolerant quantum computation is implemented using QAP structure, then computation reliability is improved, but device complexity increases due to extensive error-correcting code requirements
Solution Approach 1:
The patent employs disposable, easily regenerable cryptographic keys and encryption parameters that can be quickly generated and discarded. Instead of implementing complex, long-lived fault-tolerant quantum error correction, the system uses inexpensive, rapidly renewable cryptographic primitives that achieve similar reliability through frequent key rotation and regeneration. This approach reduces device complexity by replacing complex error correction with simpler key management.
Solution Approach 2:
The patent achieves computation reliability by dynamically adjusting cryptographic parameters such as key lengths, polynomial degrees, and noise thresholds rather than implementing fixed complex error-correcting codes. By changing these parameters adaptively based on computation depth and security requirements, the system maintains high reliability without the excessive device complexity of full fault-tolerant quantum computation architectures.
Data Source
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AI summary
A system and a method for secure multi-party exact homomorphic encryption (SMPEHE) comprising a first participant, a second participant and a third participant, wherein the system further comprises: a key generation module within the first participant to produce an encryption mapping comprising an ordered product of elementary gates; to generate a multivariate polynomial set, serving as a public encryption key, via the encryption mapping; to form an encryption operator serving as a private key; and to create an encrypted polynomial set representing a computational instruction based on an encrypted action; a message encryption module within the second participant to encode a plaintext message into a first ciphertext by the public key provided by the first participant; and to transmit the first ciphertext to the third participant; and a computation module within the third participant to receive the first ciphertext; and to perform a computation on the received first ciphertext by evaluating the encrypted polynomial set. The structure of SMPEHE is a multipartite extension of the framework EHE and protects information for multiple users across all stages from transmission, to processing and to storage. All attributes of EHE are inherited and generalized in SMPEHE, including the safeguard of both data and operations, exact encrypted computations as well as exact decryptions, blind computation, the fulfillments of quantum resilience and hyper quantum resilience, and the capabilities of performing large-scale and sophisticated encrypted computations. This structure is also deployable on CPU and GPU environments.