A Survey on Security, Privacy and Trust in Mobile Crowdsourcing

Wei Feng, Zheng Yan, Hengrun Zhang, Kai Zeng, Yu Xiao, Thomas Hou

Research output: Contribution to journalArticleScientificpeer-review

55 Citations (Scopus)
286 Downloads (Pure)

Abstract

With the popularity of sensor-rich mobile devices (e.g., smart phones and wearable devices), Mobile Crowdsourcing (MCS) has emerged as an effective method for data collection and processing. Compared with traditional Wireless Sensor Networking (WSN), MCS holds many advantages such as mobility, scalability, cost-efficiency, and human intelligence. However, MCS still faces many challenges with regard to security, privacy and trust. This paper provides a survey of these challenges and discusses potential solutions. We analyze the characteristics of MCS, identify its security threats, and outline essential requirements on a secure, privacy-preserving and trustworthy MCS system. Further, we review existing solutions based on these requirements and compare their pros and cons. Finally, we point out open issues and propose some future research directions
Original languageEnglish
Pages (from-to)2971-2992
Number of pages24
JournalIEEE Internet of Things Journal
Volume5
Issue number4
DOIs
Publication statusPublished - 2018
MoE publication typeA1 Journal article-refereed

Keywords

  • mobile crowdsourcing
  • security
  • privacy
  • trust

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