Privacy-Preserving Gross Domestic Product (GDP) Calculation Using Paillier Encryption and Differential Privacy

Privacy-Preserving Gross Domestic Product (GDP) Calculation Using Paillier Encryption and Differential Privacy

연구 분야: Cryptography

학회: ACMSE '24: Proceedings of the 2024 ACM Southeast Conference

Gross Domestic Product (GDP) is the total value of goods and services provided by a country for a period of time like one year. It is well known and is widely used by most countries to measure their economy. Various methodologies are used for GDP computation including three major approaches: (i) production, (ii) expenditure, and (iii) income. However, the practical application of these methodologies to actual country-level GDP assessment remains unsatisfied due to inherent limitations in accessing individual-level data. This paper studies the intricacies of GDP calculation, particularly focusing on the income approach. It explores innovative methods to ensure the privacy of participants in this computation, presenting techniques involving encryption and differential privacy. Experiment results show the proposed methods are promising and strongly protect individuals' privacy. This endeavor is groundbreaking, marking the first attempt to calculate GDP and related values while safeguarding contributors' privacy.