FHECipher: 可编程自举算子、CKKS 张量运算加速与全程密态 AI 推理引擎

FHECipher 设计并扩展基于格的完全同态加密 (FHE) 密码系统（CKKS、BFV、BGV、TFHE），赋能零信任机密云计算，确保敏感数据在密文计算处理全生命周期中保持高强度数学保护。

FHECipher 系统架构

Core cryptographic topology and protocol interaction of fhecipher.com

Central System: FHE Compute Core - Lattice Ring Engine

Cryptographic Nodes

  • CKKS Scheme
  • TFHE Gate
  • Bootstrapping
  • GPU Coprocessor
  • Encrypted ML

Architectural Layers & Protocols

  • Mathematical Ring Learning With Errors (RLWE) (R_Q = Z_Q[X]/(X^N + 1) with Giant Moduli (up to 1200 bits)): Encoding floating-point vectors and integers into complex polynomial coefficients
  • FHE Scheme Implementations (CKKS / BFV / TFHE) (Approximate and Exact Homomorphic Arithmetic Engines): Evaluating tensor linear algebra (CKKS) and boolean logic gates (TFHE) over ciphertexts
  • Bootstrapping & Noise Management (Algorithmic Noise Refreshing for Arbitrary Circuit Depth): Resetting accumulated polynomial noise to enable infinite deep neural network evaluation
  • Hardware Acceleration & GPU Offload (NVIDIA CUDA / AMD ROCm / Custom ASIC FHE Accelerators): Accelerating 1024-bit integer NTTs to achieve real-time encrypted AI inference

Key Metrics: Zero-Leak (Memory Plaintext Exposure) | N = 65,536 (Polynomial Ring Dimension) | Hardware Accel (Bootstrapping Acceleration) | Indistinguishable (Ciphertext Security Guarantee)

密码学的圣杯：在加密数据上直接计算

Classical encryption protects data in transit and at rest, but exposes plaintext in memory during processing. FHE leverages high-dimensional Ring Learning With Errors (RLWE) lattices to perform additions and multiplications directly on ciphertexts.

Core Engineering Areas

Technical Articles

Related Cluster Architecture Specifications