Title: An overview of location privacy protection in spatial crowdsourcing platforms during the task assignment process

Authors: Amal Abduallah Nasser Albilali; Maysoon Abulkhair; Manal Sarhan Bayousef

Addresses: Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia ' Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia ' Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia

Abstract: The field of spatial crowdsourcing (SC) has become a hot topic in recent years. The greatest concern of participants of SC platforms is privacy leakage during the task assignment (TA) process. In this study, we present an overview of techniques used to protect worker's location privacy and associate these with the directed attacks that occur during TA on SC platforms to guide researchers and enhance the development of new approaches. The overview involves analysis of major studies published in highly ranked journals during 2017-2022 and includes discussion of each technique's strengths and limitations, highlighting the attack types that threaten worker privacy and have not yet been sufficiently investigated. Finally, we present the challenges facing privacy in SC and future directions for developing advanced approaches that protect the worker privacy against critical attacks.

Keywords: spatial crowdsourcing; SC; location privacy; location protection; privacy; crowdsourcing; location attacks.

DOI: 10.1504/IJSN.2023.135509

International Journal of Security and Networks, 2023 Vol.18 No.4, pp.227 - 244

Received: 21 Feb 2023
Accepted: 25 Jun 2023
Published online: 15 Dec 2023 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article