Solving Data Trading Dilemma with Asymmetric Incomplete Information Using Zero-Determinant Strategy

Korn Sooksatra, Wei Li, Bo Mei, Arwa Alrawais, Shengling Wang, Jiguo Yu

Abstract: Trading data between user and service provider is a promising and efficient method to promote information exchange, service quality improvement, and development of emerging applications, benefiting individual and society. Meanwhile, data resale (i.e., data secondary use) is one of the most critical privacy issues hindering the ongoing process of data trading, which, unfortunately, is ignored in many of the existing privacy-preserving schemes. In this paper, we tackle the issue of data resale from a special angle, i.e., promoting cooperation between user and service provider to prevent data secondary use. For this purpose, we design a novel game-theoretical algorithm, in which user can unilaterally persuade service provider to cooperate in data trading, achieving a “win-win” situation. Besides, we validate our proposed algorithm performance through in-depth theoretical analysis and comprehensive simulations.