An Insurance-based Framework Against Security Threat in Mobile Crowdsourcing Systems

Zhao, Rong1; Jiang, Linshan2; Zhang, Kaiyue1; Zhang, Jin1

10.1109/ICPADS.2018.00051

2018

1521-9097

978-1-5386-7309-6

2018 IEEE 24TH INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED SYSTEMS (ICPADS 2018)

2018-December

322-329

11-13 Dec. 2018

Singapore, Singapore

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

Mobile crowdsourcing is a popular computing paradigm that enables smart devices to measure and collect various sensing data. When the users participate in the sensing platform, they may face various attacks and fall in a non-secure environment. Under the malicious attack, the sensing data which should be transmitted to the platform may suffer from data loss, which reduces the users' utility and platform's utility. The data loss can also lead to the reduction of the users' participatory motivations because they are not able to earn expected money due to data loss. Therefore, the total sensing quality and the social welfare will be affected eventually. To solve this problem, in Ibis paper, we propose a novel insurance-based framework to compensate the data loss due to security threat in mobile crowdsourcing systems. This framework can motivate the users with high-security levels to participate in the crowdsourcing system, thus improves the platform's utility. We formulate our framework as a Stackelberg game, where the platform is a leader and the users are followers. The theoretical analysis shows that the Nash Equilibrium exists in our framework and it can maximize the platform's revenue while considering the users' participatory willingness. Simulation results show that our framework achieves more participators, more platform's utility and social welfare, compared with existing mechanism.

Crowdsourcing stackelberg game incentive mechanism insurance

第一 ; 通讯

英语

CPCI-S ; EI

Shenzhen Science, Technology and Innovation Commission Basic Research Project[JCYJ 20160531190935987]

Computer Science

Computer Science, Hardware & Architecture

WOS:000462962600040

20191306689323

Crowdsourcing ; Insurance ; Network security ; Security systems

Computer Software, Data Handling and Applications:723 ; Accidents and Accident Prevention:914.1

Web of Science

1.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen, Peoples R China
2.Nanyang Technol Univ, Dept Comp Sci & Engn, Singapore, Singapore

Zhao, Rong,Jiang, Linshan,Zhang, Kaiyue,et al. An Insurance-based Framework Against Security Threat in Mobile Crowdsourcing Systems[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2018:322-329.