Infinite Lattice Encryption for Parallel Homomorphic Computing
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Solution Overview
Problem
Existing homomorphic encryption schemes face performance inefficiencies, incompatibility with hardware accelerators, and noise/error accumulation, limiting their application in industries requiring robust encryption and homomorphic computing, such as machine learning and artificial intelligence.
Innovation Solution
Implementing infinite lattice encryption that encrypts the field or space defined by a metric, rather than individual elements, allowing operations to be performed in parallel within an encrypted field, maintaining relative distances and reducing computational complexity, and using robust encryption algorithms to secure the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing homomorphic encryption schemes are used, then data security is maintained, but computational performance is vastly slower than equivalent computations on plaintext
Solution Approach 1:
The patent segments the encryption approach by transitioning from element-wise encryption to field encryption, where the entire field defined by a metric is encrypted as a unified structure. This segmentation allows parallel processing of multiple elements within the encrypted field simultaneously, dramatically improving computational performance while maintaining security through the underlying lattice cryptography structure.
Solution Approach 2:
The patent introduces a new dimension of encryption by operating on encrypted fields rather than individual encrypted elements. This dimensional shift from scalar to field-level operations enables vectorized and matrix-based computations on encrypted data, achieving performance improvements comparable to plaintext operations while preserving data confidentiality.
2Reliability
If existing homomorphic encryption schemes are used, then encryption is provided, but compatibility with hardware accelerators is lost
Solution Approach 1:
The patent replaces the mechanical sequential processing model with a field-based parallel processing model that is inherently compatible with hardware accelerator architectures. By structuring encrypted data as fields with preserved geometric relationships, the system enables SIMD (Single Instruction Multiple Data) operations and other hardware-accelerated parallel computations, bridging the gap between cryptographic security and hardware performance.
3Adaptability or versatility
If existing homomorphic encryption schemes are used, then limited encryption operations are supported, but error accumulation occurs with each operation on ciphertext
Solution Approach 1:
The patent merges multiple encrypted elements into a unified encrypted field structure, where operations are performed on the entire field simultaneously. This merging approach consolidates error management at the field level rather than accumulating errors from sequential element operations, reducing overall error accumulation while supporting a broader range of cryptographic operations including comparison, sorting, and aggregation functions.
Data Source
AI summary
An infinite lattice encryption (ILC) can include encrypting an entire, as opposed to individual, or bit-by-bit, encryption of the elements in the field. String data can be converted to high-entropy quantitative data, for example, a two-dimensional vector and encrypted using the described encryption algorithm. The conversion can preserve the collation order of the string if one dimension of the quantitative data is from a sorted set of random numbers. Executables, such as computer programs, can be encrypted using ILC. The computer program can be turned into a graph of operations, where each edge can be replaced, based on a number randomly chosen from an encryption co-domain. The numerical and string data in the graph can be encrypted using the described ILC techniques.