Paper 2025/1873

Threshold Reporting Protocol for Traceability in Anonymous Social Networks

Abstract

As anonymous social networks continue to grow in popularity, they raise serious challenges around abuse, misinformation, and harmful behavior. While traditional de-anonymization techniques can address misuse, they often come at the cost of user privacy. Protecting honest users' privacy while keeping malicious ones accountable remains a complex challenge. A promising alternative is conditional deanonymization, where anonymity is lifted only when abuse is collectively reported and verified by an authority. In this work, we present a new cryptographic framework for conditional de-anonymization that preserves user anonymity unless a threshold number of validated abuse reports is reached. Our design leverages threshold cryptography to ensure that de-anonymization can only be triggered under well-defined, collectively enforced conditions—resisting false reports, misuse, and collusion. We formalize the model and provide a generic construction from standard cryptographic primitives, proving strong security guarantees even in the presence of adversarial authorities or malicious users. To illustrate its viability, we also propose a concrete instantiation based on lattice-based assumptions, making it a compelling candidate for post-quantum settings.