Paper 2026/1723

De-SyRIS: A Decentralized Sybil-Resistant Identity System Using Mutual Facial Biometric Verification and Social Graph Analysis

Abstract

While decentralized identity management systems strive for autonomy, most still rely on centralized mechanisms (e.g., phone numbers or government-issued IDs) to achieve Sybil resistance and prevent fake identity attacks. This article proposes a novel approach for decentralized identity management that ensures robust Sybil resistance, unlike the systems currently in widespread use. Our approach is based on a social graph of connected users. The main novelty resides in pairwise mutual facial biometric verification for connected users and anti-Sybil social graph analysis. By leveraging blockchain technology, zero-knowledge proofs, and privacy-preserving smart contract platforms, the system ensures the uniqueness, anonymity, and privacy of registered users without relying on centralized authorities. We implemented a proof-of-concept prototype of our approach using fast Plonky2 zero-knowledge proofs and evaluated its functionality through simulations on heterogeneous social graph models with 1000 entities. To the best of our knowledge, this is the first work to propose a Sybil-resistant identity system that neither sacrifices decentralization nor privacy and does not rely on any centralized credential issuers.