Permissioned Blockchain-based Framework for Ranking Synthetic Data Generators

Narasimha Raghavan Veeraragavan; Mohammad Hossein Tabatabaei; Severin Elvatun; Vibeke Binz Vallevik; Siri Larønningen; Jan F Nygård

arXiv · 2405.07196

Permissioned Blockchain-based Framework for Ranking Synthetic Data Generators

Narasimha Raghavan Veeraragavan·Mohammad Hossein Tabatabaei·Severin Elvatun·Vibeke Binz Vallevik·Siri Larønningen·Jan F Nygård

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Abstract

Synthetic data generation is increasingly recognized as a crucial solution to address data related challenges such as scarcity, bias, and privacy concerns. As synthetic data proliferates, the need for a robust evaluation framework to select a synthetic data generator becomes more pressing given the variety of options available. In this research study, we investigate two primary questions: 1) How can we select the most suitable synthetic data generator from a set of options for a specific purpose? 2) How can we make the selection process more transparent, accountable, and auditable? To address these questions, we introduce a novel approach in which the proposed ranking algorithm is implemented as a smart contract within a permissioned blockchain framework called Sawtooth. Through comprehensive experiments and comparisons with state-of-the-art baseline ranking solutions, our framework demonstrates its effectiveness in providing nuanced rankings that consider both desirable and undesirable properties. Furthermore, our framework serves as a valuable tool for selecting the optimal synthetic data generators for specific needs while ensuring compliance with data protection principles.

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Narasimha Raghavan Veeraragavan, Mohammad Hossein Tabatabaei, Severin Elvatun, Vibeke Binz Vallevik, Siri Larønningen, Jan F Nygård. 2024-05-12. Permissioned Blockchain-based Framework for Ranking Synthetic Data Generators. https://arxiv.org/abs/2405.07196

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