Privacy-Preserving User Recruitment Protocol for Mobile Crowdsensing

Published on Feb 6, 2020in IEEE ACM Transactions on Networking3.597
· DOI :10.1109/TNET.2019.2962362
Mingjun Xiao15
Estimated H-index: 15
(USTC: University of Science and Technology of China),
Guoju Gao6
Estimated H-index: 6
(USTC: University of Science and Technology of China)
+ 2 AuthorsLiusheng Huang27
Estimated H-index: 27
(USTC: University of Science and Technology of China)
Mobile crowdsensing is a new paradigm in which a requester can recruit a group of mobile users via a platform and coordinate them to perform some sensing tasks by using their smartphones. In mobile crowdsensing, each user might perform multiple tasks with different sensing qualities. Meanwhile, the users participating in the crowdsensing will ask for sufficient rewards to compensate for their expenditures. Hence, an important problem is how to recruit the users with minimum cost while achieving a satisfactory sensing quality for each task. Furthermore, in order to ease users’ worries about privacy disclosures, the user recruitment process needs to protect each user’s sensing quality and recruitment cost information from being revealed to other users or to the platform. In this paper, we propose two secure user recruitment problems for the cases where the recruitment costs of users are homogeneous and heterogeneous. After proving the NP-hardness of the problems, we design two secure user recruitment protocols by using secret sharing scheme. Both of the proposed protocols adopt greedy strategies, which can recruit nearly optimal users while ensuring that the total sensing quality of each task is no less than a given threshold. The difference lies in that the two greedy strategies are based on two unique utility functions. We analyze the approximation ratios of the two protocols and prove the security under the semi-honest model. Finally, we demonstrate the significant performance of the proposed protocols through extensive simulations and executions on real smartphones.
  • References (33)
  • Citations (0)
📖 Papers frequently viewed together
2017INFOCOM: International Conference on Computer Communications
4 Authors (Mingjun Xiao, ..., Jiapeng Yu)
23 Citations
2019GLOBECOM: Global Communications Conference
6 Authors (Liang Li, ..., Miao Pan)
2016GLOBECOM: Global Communications Conference
4 Authors (Mengyuan Zhang, ..., Junshan Zhang)
8 Citations
78% of Scinapse members use related papers. After signing in, all features are FREE.
#1Guoju Gao (USTC: University of Science and Technology of China)H-Index: 6
#2Mingjun Xiao (USTC: University of Science and Technology of China)H-Index: 15
Last. Chang Hu (USTC: University of Science and Technology of China)H-Index: 6
view all 5 authors...
In this paper, we focus on the incentive mechanism design for a vehicle-based, nondeterministic crowdsensing system. In this crowdsensing system, vehicles move along their trajectories and perform corresponding sensing tasks with different probabilities. Each task may be performed by multiple vehicles jointly so as to ensure a high probability of success. Designing an incentive mechanism for such a crowdsensing system is challenging since it contains a non-trivial set cover problem. To solve thi...
8 CitationsSource
#1Miao Hu (Beijing Jiaotong University)H-Index: 5
#2Zhong Zhangdui (Beijing Jiaotong University)H-Index: 36
Last. Minming Ni (Beijing Jiaotong University)H-Index: 10
view all 4 authors...
For urban crowdsourcing applications, the data sensing tasks can be achieved by vehicles traveling on the roads, which can save the expenses on constructing dedicated infrastructures. In this paper, to efficiently handle the crowdsourcing recruitment problem, we propose to recruit participants with the duration-variable principle and prove that it performs better compared to the strategy that recruits vehicles for all required time periods. The duration-variable principle enables recruitment of ...
1 CitationsSource
May 1, 2017 in INFOCOM (International Conference on Computer Communications)
#1Mingjun Xiao (USTC: University of Science and Technology of China)H-Index: 15
#2Jie Wu (TU: Temple University)H-Index: 99
Last. Jiapeng Yu (USTC: University of Science and Technology of China)H-Index: 1
view all 4 authors...
23 CitationsSource
#1Yanyan Han (University of Louisiana at Lafayette)H-Index: 5
#2Tie Luo (Agency for Science, Technology and Research)H-Index: 16
Last. Hongyi Wu (University of Louisiana at Lafayette)H-Index: 31
view all 4 authors...
Device-to-Device (D2D) networks impose a significant challenge on delay-sensitive crowdsourcing due to the highly non-deterministic and intermittent network connectivity. Under this setting, the paper investigates a participant recruitment problem in which an initial set of recruited nodes, which we call seeds , need to make an optimal decision on what other nodes to recruit to perform the crowdsourcing task. These seeds face the dilemma that recruiting more nodes increases their own payment but...
13 CitationsSource
#1Avhishek Chatterjee (UIUC: University of Illinois at Urbana–Champaign)H-Index: 6
#2Michael Borokhovich (University of Texas at Austin)H-Index: 10
Last. Sriram Vishwanath (University of Texas at Austin)H-Index: 39
view all 4 authors...
Many companies now use crowdsourcing to leverage external (as well as internal) crowds to perform specialized work, and so methods of improving efficiency are critical. Tasks in crowdsourcing systems with specialized work have multiple steps and each step requires multiple skills. Steps may have different flexibilities in terms of obtaining service from one or multiple agents, due to varying levels of dependency among parts of steps. Steps of a task may have precedence constraints among them. Mo...
8 CitationsSource
#1Xiaocong Jin (ASU: Arizona State University)H-Index: 9
#2Yanchao Zhang (ASU: Arizona State University)H-Index: 37
Crowdsourced spectrum sensing has great potential in improving current spectrum database services. Without strong incentives and location privacy protection in place, however, mobile users will be reluctant to act as mobile crowdsourcing workers for spectrum sensing tasks. In this paper, we present PriCSS, the first framework for a crowdsourced spectrum sensing service provider to select spectrum-sensing participants in a differentially privacy-preserving manner. Thorough theoretical analysis an...
31 CitationsSource
#1Honggang Zhang (University of Massachusetts Boston)H-Index: 17
#2Benyuan Liu (University of Massachusetts Lowell)H-Index: 30
Last. Tong Sun (University of Massachusetts Lowell)H-Index: 5
view all 5 authors...
We investigate emerging proximity-based Mobile Crowd Service or pMCS systems, in which services are provided and consumed by users carrying smart mobile devices (e.g., smartphones) and in proximity of each other (e.g., within Bluetooth range). Due to limited resources on smartphones, it is crucial to provide a mechanism to incentivize users' participation and ensure fair trading in a pMCS system. In this paper, we design a multi-market dynamic double auction mechanism for a pMCS system, referred...
32 CitationsSource
#1Lingjun Pu (NKU: Nankai University)H-Index: 8
#2Xu Chen (GAU: University of Göttingen)H-Index: 26
Last. Xiaoming Fu (GAU: University of Göttingen)H-Index: 30
view all 4 authors...
In this paper, we advocate Crowdlet, a novel self-organized mobile crowdsourcing paradigm, in which a mobile task requester can proactively exploit a massive crowd of encountered mobile workers at real-time for quick and high-quality results. We present a comprehensive system model of Crowdlet that defines task, worker arrival and worker ability models. Further, we introduce a service quality concept to indicate the expected service gain that a requester can enjoy when he recruits an encountered...
38 CitationsSource
#1Qian Wang (WHU: Wuhan University)H-Index: 32
#2Yan Zhang (WHU: Wuhan University)H-Index: 4
Last. Kui Ren (UB: University at Buffalo)H-Index: 63
view all 6 authors...
Nowadays gigantic crowd-sourced data collected from mobile phone users have become widely available, which enables the possibility of many important data mining applications to improve the quality of our daily lives. While providing tremendous benefits, the release of these data to the public will pose a considerable threat to mobile users' privacy. To solve this problem, the notion of differential privacy has been proposed to provide privacy with theoretical guarantee, and recently it has been ...
32 CitationsSource
#1Gaoqiang Zhuo (Binghamton University)H-Index: 3
#2Qi Jia (Binghamton University)H-Index: 5
Last. Pan Li (Case Western Reserve University)H-Index: 29
view all 5 authors...
Crowdsourcing is a crowd-based outsourcing, where a requester (task owner) can outsource tasks to workers (public crowd). Recently, mobile crowdsourcing, which can leverage workers' data from smartphones for data aggregation and analysis, has attracted much attention. However, when the data volume is getting large, it becomes a difficult problem for a requester to aggregate and analyze the incoming data, especially when the requester is an ordinary smartphone user or a start-up company with limi...
28 CitationsSource
Cited By0