{"slug": "ghostfacempc-privacy-preserving-face-recognition-with-multi-party-computation", "title": "GhostFaceMPC: Privacy-Preserving Face Recognition with Multi-Party Computation", "summary": "Researchers released GhostFaceMPC, described as the first end-to-end privacy-preserving face recognition system to evaluate a deep convolutional neural network extractor and matching under secure multi-party computation, with code available at https://github.com/crypto-unict/GhostFaceMPC. The system processes facial data across feature extraction, storage and matching without exposing raw images or biometric embeddings at any stage, using a multi-party computation-friendly quantization of the GhostFaceNet model plus circuit optimizations to make recognition under multi-party computation practical.", "body_md": "Facial recognition has become central to modern authentication systems, security frameworks, and personalized services. However, its widespread adoption is hindered by severe privacy risks, particularly surrounding unauthorized access to sensitive biometric data. To address these challenges, this paper presents GhostFaceMPC, the first end-to-end, privacy-preserving face recognition system to evaluate a deep convolutional neural network extractor and matching under secure multi-party computation. GhostFaceMPC enables secure processing of facial data across all stages of a face recognition process, from feature extraction and storage to matching, without exposing raw images or biometric embeddings at any stage.\nWe introduce a multi-party computation-friendly quantization of the GhostFaceNet model and circuit optimizations that make face recognition under multi-party computation practical. The code is available at https://github.com/crypto-unict/GhostFaceMPC.", "url": "https://wpnews.pro/news/ghostfacempc-privacy-preserving-face-recognition-with-multi-party-computation", "canonical_source": "https://eprint.iacr.org/2026/2499", "published_at": "2026-10-15 17:33:21+00:00", "updated_at": "2026-10-15 19:56:28.122328+00:00", "lang": "en", "topics": ["computer-vision", "ai-safety", "ai-research", "machine-learning"], "entities": ["GhostFaceMPC", "GhostFaceNet", "crypto-unict"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/ghostfacempc-privacy-preserving-face-recognition-with-multi-party-computation", "markdown": "https://wpnews.pro/news/ghostfacempc-privacy-preserving-face-recognition-with-multi-party-computation.md", "text": "https://wpnews.pro/news/ghostfacempc-privacy-preserving-face-recognition-with-multi-party-computation.txt", "jsonld": "https://wpnews.pro/news/ghostfacempc-privacy-preserving-face-recognition-with-multi-party-computation.jsonld"}}