On the Usage of Verifiable Credentials in Privacy-Preserving Federated Analytics

arXiv:2609.33004 · cs.CR, cs.ET · Submitted 2026-09-26 · Read on arXiv

cs.CR, cs.ET

Submitted: 2026-09-26

Updated: 2026-09-26

License: http://creativecommons.org/licenses/by/4.0/

The gist: Privacy-Preserving Federated Analytics enables multiple nodes to collaboratively derive statistical insights without exchanging raw data.

Terminology

Federated Analytics — 9× in this paper
Privacy-Preserving Federated Analytics — 5× in this paper
Self-Sovereign Identity — 5× in this paper
Verifier — 4× in this paper · explained in 2 episodes
Verification — 3× in this paper · explained in 2 episodes
Machine Learning — 2× in this paper
Verifiable Data Registry — 2× in this paper
Aggregation — 1× in this paper · explained in 1 episode
Communication Overhead — 1× in this paper · explained in 2 episodes
Differential Privacy — 1× in this paper · explained in 4 episodes
Edge Devices — 1× in this paper · explained in 2 episodes
Federated Learning — 1× in this paper · explained in 14 episodes
General Data Protection Regulation — 1× in this paper
Internet of Things — 1× in this paper
Unified Framework — 1× in this paper · explained in 5 episodes

Abstract

Privacy-Preserving Federated Analytics enables multiple nodes to collaboratively derive statistical insights without exchanging raw data. However, ensuring node authenticity and data validation (avoiding concerns such as identity tracking, data linkage, or data leakage) remain fundamental challenges. This paper offers some insights into the feasibility of defining an authenticated, integrity-preserving data model by coupling FPPA with Verifiable Credentials defined within the Self-Sovereign Identity framework.

On the Usage of Verifiable Credentials in Privacy-Preserving Federated Analytics

Terminology

Abstract

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