The popularity of Location-Based Services (LBSs) have resulted in serious privacy concerns recently. Mobile users may lose their privacy while enjoying kinds of social activities due to the untrusted LBS servers. Many Privacy Protection Mechanisms (PPMs) are proposed in literature by employing different strategies, which come at the cost of either system overhead, or service quality, or both of them. In this paper, we design privacy-preserving strategies for both of the users and adversaries in service quality aware LBSs. Different from existing approaches, we first define and point out the importance of the Fine-Grained Side Information (FGSI) over existing concept of the side information, and propose a Dual-Privacy Metric (DPM) and Service Quality Metric (SQM). Then, we build analytical frameworks that provide privacy-preserving strategies for mobile users and the adversaries to achieve their goals, respectively. Finally, the evaluation results show the effectiveness of our proposed frameworks and the strategies.