Efficient and Non-Repudiable Data Trading Scheme Based on State Channels and Stackelberg Game

As the Internet of Things gathers pace and popularity, more and more data is collected at the edge. To unleash the value of data and make it tradable, data markets have been proposed. However, existing data markets generally depend on broker or blockchain, which inevitably raises concerns about one or more aspects of fairness, security, or efficiency. In addition, to promote data trading in the data market, a data trading incentive mechanism is also essential. In this paper, we propose a novel data trading scheme based on state channels and Stackelberg game. First, we propose a State Channels-based Data Trading (SCDT) framework to support non-repudiable and efficient data trading. The framework can arbitrate disputes arising from off-chain data trading through state channels, enabling traders to conduct efficient transactions off-chain without worrying about security issues. Second, we propose an optimal incentive mechanism to solve the pricing and purchasing problems. The tripartite interactions among the data seller, resource seller, and user service platform are formulated as a Stackelberg game to maximize the profits of all participants. Finally, we implement the data trading framework and analyze the incentive mechanism, which reveals the feasibility of the framework and the rationality of the incentive mechanism.