论文信息 - IM-LDP: Incentive Mechanism for Mobile Crowd-Sensing Based on Local Differential Privacy - 字舞流文

IM-LDP: Incentive Mechanism for Mobile Crowd-Sensing Based on Local Differential Privacy

Yantao Li | Hongyu Huang | Dan Chen | Hongyu Huang | Yantao Li | Dan Chen

[1] Zhetao Li,et al. Towards Privacy-preserving Incentive for Mobile Crowdsensing Under An Untrusted Platform , 2019, IEEE INFOCOM 2019 - IEEE Conference on Computer Communications.

[2] Klara Nahrstedt,et al. Incentive Mechanism for Privacy-Aware Data Aggregation in Mobile Crowd Sensing Systems , 2018, IEEE/ACM Transactions on Networking.

[3] Cynthia Dwork,et al. Differential Privacy: A Survey of Results , 2008, TAMC.

[4] Xintao Wu,et al. Using Randomized Response for Differential Privacy Preserving Data Collection , 2016, EDBT/ICDT Workshops.

[5] Lei Yang,et al. Crowd-Empowered Privacy-Preserving Data Aggregation for Mobile Crowdsensing , 2018, MobiHoc.

[6] Yantao Li,et al. A Real-Time Data Collection Mechanism With Trajectory Privacy in Mobile Crowd-Sensing , 2020, IEEE Communications Letters.

[7] Ju Ren,et al. Towards Pattern-aware Privacy-preserving Real-time Data Collection , 2020, IEEE INFOCOM 2020 - IEEE Conference on Computer Communications.

[8] Yuanqing Xia,et al. Quality-aware incentive mechanism based on payoff maximization for mobile crowdsensing , 2018, Ad Hoc Networks.

[9] S L Warner,et al. Randomized response: a survey technique for eliminating evasive answer bias. , 1965, Journal of the American Statistical Association.