| Summary: | 碩士 === 國立臺灣科技大學 === 資訊工程系 === 102 === Due to increasing sensing capacity, smartphones offer opportunity to monitor human activity. By combining traditional sensors deployed in fixed positions and sensors embedded in smartphones carried by human, a new paradigm of sensing, named mobile sensing, is introduced. In particular, the mobile users act as queriers who request information provided by the mobile users who act as data collectors, and the data collection and delivery are facilitated by human mobility and ubiquity. However, human factors involving in mobile sensing rises additional privacy considerations. This thesis respectively exploits group and identity-based signatures to preserve privacy of information supported by fixed sensors and smartphones. However, the complicated computation of group signatures mounts workloads on resource-limited smartphones. We therefore group the mobile users according to their current positions rather than the information type they queried. The physical proximity feature of human makes a low frequency of joining and leaving a group in our regional grouping approach, thereby reducing the computation overheads and delay in group signature. We implement group signature on the smartphone and conduct a simulation experiment to investigate the performance of proposed regional grouping approach. The simulation results show that the regional grouping approach is more efficient than traditional one grouped by information type.
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