CRYPTOGRAPHIC METHODS OF ZEROKNOWLEDGE PROOF AS A DRIVER OF INFORMATION ASYMMETRY IN DATA MARKETS

Abstract

The article examines cryptographic methods of zero-knowledge proof (ZKP) as a tool for overcoming information asymmetry in data markets. The theoretical foundations of ZKP are considered, including their formal properties and classification, as well as practical application scenarios in digital identification systems, confidential auctions, machine learning and data management. The impact of ZKP on the behavior of economic agents, transaction costs and market structure is analyzed. Both potential benefits of the technology — increased trust and automated verification — and risks associated with computational complexity and possible participant segmentation are identified. The study concludes that further development of hybrid privacy architectures and regulatory mechanisms is necessary to support open data markets.