Privacy protection in mobile crowd sensing: a survey

• DOI: 10.1007/s11280-019-00745-2
• Publication Date: 2019-11-20T22:01:38Z
• Authors: Yongfeng Wang; Zheng Yan; Wei Feng; Shushu Liu
• Keywords: Popularity; Viewpoints; Privacy software

Abstract The unprecedented proliferation of mobile smart devices has propelled a promising computing paradigm, Mobile Crowd Sensing (MCS), where people share surrounding insight or personal data with others. As fast, easy, and cost-effective way to address large-scale societal problems, MCS is widely applied into many fields, e.g., environment monitoring, map construction, public safety, etc. Despite the popularity, risk sensitive information disclosure in poses serious threat participants limits its further development privacy-sensitive fields. Thus, research on privacy protection becomes important urgent. This paper targets issues conducts comprehensive literature it by providing thorough survey. We first introduce typical system structure MCS, summarize characteristics, propose essential requirements basis model. Then, we survey existing solutions evaluate their performances employing proposed requirements. In essence, classify schemes four categories regard identity privacy, attribute task privacy. Besides, review achievements privacy-preserving incentives from viewpoints incentive measures: credit incentive, auction currency reputation incentive. Finally, point out some open future directions based findings our