Visible to the public Service Quality Loss-aware Privacy Protection Mechanism in Edge-Cloud IoTs

TitleService Quality Loss-aware Privacy Protection Mechanism in Edge-Cloud IoTs
Publication TypeConference Paper
Year of Publication2021
AuthorsSun, Zice, Wang, Yingjie, Tong, Xiangrong, Pan, Qingxian, Liu, Wenyi, Zhang, Jiqiu
Conference Name2021 13th International Conference on Advanced Computational Intelligence (ICACI)
Keywordscontrol theory, crowdsourcing, game theory, Games, Human Behavior, incentive mechanism, localized differential privacy, Market research, privacy, privacy protection, Propagation losses, pubcrawl, Repeated game, resilience, Resiliency, Scalability, Sensors, Servers
AbstractWith the continuous development of edge computing, the application scope of mobile crowdsourcing (MCS) is constantly increasing. The distributed nature of edge computing can transmit data at the edge of processing to meet the needs of low latency. The trustworthiness of the third-party platform will affect the level of privacy protection, because managers of the platform may disclose the information of workers. Anonymous servers also belong to third-party platforms. For unreal third-party platforms, this paper recommends that workers first use the localized differential privacy mechanism to interfere with the real location information, and then upload it to an anonymous server to request services, called the localized differential anonymous privacy protection mechanism (LDNP). The two privacy protection mechanisms further enhance privacy protection, but exacerbate the loss of service quality. Therefore, this paper proposes to give corresponding compensation based on the authenticity of the location information uploaded by workers, so as to encourage more workers to upload real location information. Through comparative experiments on real data, the LDNP algorithm not only protects the location privacy of workers, but also maintains the availability of data. The simulation experiment verifies the effectiveness of the incentive mechanism.
DOI10.1109/ICACI52617.2021.9435865
Citation Keysun_service_2021