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REAP: An Efficient Incentive Mechanism for Reconciling Aggregation
  Accuracy and Individual Privacy in Crowdsensing

REAP: An Efficient Incentive Mechanism for Reconciling Aggregation Accuracy and Individual Privacy in Crowdsensing

2 November 2017
Zhikun Zhang
Shibo He
Jiming Chen
Junshan Zhang
ArXiv (abs)PDFHTML

Papers citing "REAP: An Efficient Incentive Mechanism for Reconciling Aggregation Accuracy and Individual Privacy in Crowdsensing"

2 / 2 papers shown
Title
DPCrowd: Privacy-preserving and Communication-efficient Decentralized
  Statistical Estimation for Real-time Crowd-sourced Data
DPCrowd: Privacy-preserving and Communication-efficient Decentralized Statistical Estimation for Real-time Crowd-sourced Data
Xuebin Ren
Chia-Mu Yu
Wei Yu
Xinyu Yang
Jun Zhao
Shusen Yang
58
6
0
29 Sep 2020
Duplicity Games for Deception Design with an Application to Insider
  Threat Mitigation
Duplicity Games for Deception Design with an Application to Insider Threat Mitigation
Linan Huang
Quanyan Zhu
164
25
0
14 Jun 2020
1