FHEID: Zero-Leakage biometrische Templates, verschlüsselte Embedding-Suche & private Beweise

FHEID Homomorphic Biometric Pipeline & Cloud Matching Topology

Client biometric extraction, CKKS homomorphic encryption, and blind cloud similarity search

Central System: FHE Biometric Engine - Encrypted Vector Matching Core

Cryptographic Nodes

• Client Feature Extractor
• CKKS Homomorphic Encrypter
• Untrusted Cloud Matcher
• Encrypted Threshold Evaluator
• Client Decision Decryptor

Architectural Layers & Protocols

• Client Biometric Extraction Plane (Edge Neural Network / Secure Enclave): Extracting normalized 512-element floating-point feature embeddings from iris, face, or fingerprint sensors.
• Homomorphic Vector Cryptosystem (CKKS Ring-LWE Homomorphic Encryption): Encrypting biometric embeddings into high-degree polynomial rings with configurable noise budgets.
• Blind Cloud Evaluation Engine (SIMD Vector Batching & Rescaling Operations): Computing encrypted dot products across millions of stored encrypted templates in parallel without decryption.
• Privacy Compliance & Audit Layer (GDPR Article 9 / CCPA / BIPA Biometric Shield): Guaranteeing mathematical impossibility of biometric template reconstruction from stolen databases.

Key Metrics: Zero Decryption (Cloud Biometric Privacy) | < 85 ms (Homomorphic Match Time) | 512 Dimensions (Vector Embedding Size) | 100% (GDPR / BIPA Compliance)