Privacy preservation has been one of the biggest concerns in data sharing and publishing. The wide-spread application of data sharing and publishing contributes to the utilization of data, but brings a severe risk of privacy leakage. Although the corresponding privacy preservation techniques have been proposed, it is inevitable to decrease the accuracy of data. More importantly, it is a challenge to analyze the behaviors and interactions among different participants, including data owners, collectors and adversaries. For data owners and collectors, they need to select proper privacy preservation mechanisms and parameters to maximize their utility under a certain amount of privacy guarantee. For data adversaries, their objective is to get the sensitive information by various attack measurements. In this paper, we survey the related work of game theory-based privacy preservation under data sharing and publishing. We also discuss the possible trends and challenges of the future research. Our survey provides a systematic and comprehensive understanding about privacy preservation problems under data sharing and publishing.