FHECipher: Amorçage Programmable, Opérations Tensorielles CKKS et Inférence Chiffrée

FHECipher conçoit et déploie des cryptosystèmes de chiffrement totalement homomorphe (FHE) basés sur les réseaux euclidiens (CKKS, BFV, BGV, TFHE), permettant un calcul cloud confidentiel zero-trust où les données restent mathématiquement protégées en cours de traitement.

FHECipher System Architecture

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)

Le Saint Graal de la cryptographie : calculer sur des données chiffrées

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