CSWA: Aggregation-Free Spatial-Temporal Community Sensing

Bian, Jiang (Missouri University of Science and Technology) | Xiong, Haoyi (Missouri University of Science and Technology) | Fu, Yanjie (Missouri University of Science and Technology) | Das, Sajal K. (Missouri University of Science and Technology)

AAAI Conferences 

According to (Zhang et Though compressive community sensing can effectively al. 2014a), there are two major roles in community sensing reduce the required incentives and participants, it still aggregates - the organizer and the participants - where the former is the real-time location and sensor data from each the individual or organization that creates the sensing task, participant, so as to first identify the covered subareas, fill recruits participants and collects the sensor data, while the with collected data, and then recover the missing data for latter (i.e., participants) involve in the sensing task and provide the rest. To protect the location privacy of participants, the the sensing data. Frequently, the organizer pursues a same of group of researchers (Wang et al. 2017a; 2016b) proposed high (or even full) spatial-temporal coverage of the collected to leverage the Differential Geo-Obfuscation to replace sensor data. However incentives (e.g., monetary rewards) and each participants' real-time location with a "mock" location the threats to privacy (e.g., exposing real-time locations) are while insuring the recovery accuracy. With the Differential two major concerns that may affect the willingness of the Geo-Obfuscation, the participants' locations are expected to participants to join a community sensing task.

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