Privacy Protection for Multi-Option Problem of Participatory Sensing Using Random Noise Addition
The rapid proliferation of smartphone-mounted multiple sensors has been accompanied by the increasing utilization of participatory sensing, which is a type of crowdsourcing by which many users effectively share sensing data. Privacy protection is important for this purpose because the sensing data often contain private information about the users. Existing privacy protection methods do not enable effective and precise data restoration in this application when there is many choices and few data. In this study, we developed a method for addressing this issue. The randomized response method and negative survey method are used to conceal private information contained in individual data by the addition of random noise to the data. Moreover, the proposed method utilizes a novel procedure whereby the transmission is repeated multiple times when selecting one option from multiple options. The proposed method is evaluated by simulation and is found to be more effective than existing methods.
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