Poster: Privacy-Preserving Compliance Checks on Ethereum via Selective Disclosure

2026-02-20

AI Summary

This work addresses the privacy risks inherent in conventional digital identity verification, where users are often compelled to over-disclose sensitive information to meet regulatory compliance, thereby exposing themselves to surveillance and data breaches. The paper proposes the first Ethereum-based, general-purpose selective disclosure framework that decouples identity attributes from their underlying source documents by integrating client-side zk-SNARKs with smart contracts. This approach enables users to prove eligibility—such as age requirements—without revealing the original identity credentials. The framework fully supports the Grant-Verify-Revoke lifecycle of identity claims and achieves sub-200-millisecond client-side latency in practical scenarios like age verification, effectively reconciling stringent regulatory compliance with the pseudonymity guarantees of blockchain systems.

Technology Category

• Machine Learning: Privacy
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Philosophy and Ethics of AI: Privacy & Security

Application Category

• Security and Privacy: Data transparency and provenance
• Responsible Web: Data and user privacy-enhancing technologies for the Web
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

Digital identity verification often forces a privacy trade-off, where users must disclose sensitive personal data to prove simple eligibility criteria. As blockchain applications integrate with regulated environments, this over-disclosure creates significant risks of data breaches and surveillance. This work proposes a general Selective Disclosure Framework built on Ethereum, designed to decouple attribute verification from identity revelation. By utilizing client-side zk-SNARKs, the framework enables users to prove specific eligibility predicates without revealing underlying identity documents. We present a case study, ZK-Compliance, which implements a functional Grant, Verify, Revoke lifecycle for age verification. Preliminary results indicate that strict compliance requirements can be satisfied with negligible client-side latency (< 200 ms) while preserving the pseudonymous nature of public blockchains.

Problem

• privacy-preserving
• compliance checks
• selective disclosure
• digital identity verification
• blockchain

Innovation

• selective disclosure
• zk-SNARKs
• privacy-preserving compliance
• Ethereum
• digital identity verification