InPPTD: A Lightweight Incentive-Based Privacy-Preserving Truth Discovery for Crowdsensing Systems
暂无分享,去创建一个
Bin Zhu | Kaiping Xue | David S. L. Wei | Nenghai Yu | Qingyou Yang | Na Gai | Kaiping Xue | Nenghai Yu | Bin Zhu | Qingyou Yang | Na Gai
[1] Philip S. Yu,et al. Truth Discovery with Multiple Conflicting Information Providers on the Web , 2007, IEEE Transactions on Knowledge and Data Engineering.
[2] Kaigui Bian,et al. Jigsaw: indoor floor plan reconstruction via mobile crowdsensing , 2014, MobiCom.
[3] Bo Zhao,et al. Resolving conflicts in heterogeneous data by truth discovery and source reliability estimation , 2014, SIGMOD Conference.
[4] Bo Zhao,et al. A Survey on Truth Discovery , 2015, SKDD.
[5] Jing Gao,et al. Truth Discovery on Crowd Sensing of Correlated Entities , 2015, SenSys.
[6] Mohsen Guizani,et al. LPTD: Achieving Lightweight and Privacy-Preserving Truth Discovery in CIoT , 2018, Future Gener. Comput. Syst..
[7] Chenglin Miao,et al. Towards Differentially Private Truth Discovery for Crowd Sensing Systems , 2018, 2020 IEEE 40th International Conference on Distributed Computing Systems (ICDCS).
[8] Chenglin Miao,et al. An Efficient Two-Layer Mechanism for Privacy-Preserving Truth Discovery , 2018, KDD.
[9] Cong Wang,et al. Leveraging Crowdsensed Data Streams to Discover and Sell Knowledge: A Secure and Efficient Realization , 2018, 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS).
[10] Dongxiao Liu,et al. Achieving efficient and privacy-preserving truth discovery in crowd sensing systems , 2017, Comput. Secur..
[11] Pascal Paillier,et al. Public-Key Cryptosystems Based on Composite Degree Residuosity Classes , 1999, EUROCRYPT.
[12] Cong Wang,et al. Learning the Truth Privately and Confidently: Encrypted Confidence-Aware Truth Discovery in Mobile Crowdsensing , 2018, IEEE Transactions on Information Forensics and Security.
[13] Charu C. Aggarwal,et al. Recursive Ground Truth Estimator for Social Data Streams , 2016, 2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).
[14] Guihai Chen,et al. Pay as How Well You Do: A Quality Based Incentive Mechanism for Crowdsensing , 2015, MobiHoc.
[15] Klara Nahrstedt,et al. INCEPTION: incentivizing privacy-preserving data aggregation for mobile crowd sensing systems , 2016, MobiHoc.
[16] Xue Liu,et al. Generalized Decision Aggregation in Distributed Sensing Systems , 2014, 2014 IEEE Real-Time Systems Symposium.
[17] Cong Wang,et al. Privacy-Aware and Efficient Mobile Crowdsensing with Truth Discovery , 2020, IEEE Transactions on Dependable and Secure Computing.
[18] Jiantao Zhou,et al. Denoising in the Dark: Privacy-Preserving Deep Neural Network-Based Image Denoising , 2019, IEEE Transactions on Dependable and Secure Computing.
[19] Qi Li,et al. A Personalized Privacy Protection Framework for Mobile Crowdsensing in IIoT , 2020, IEEE Transactions on Industrial Informatics.
[20] Jian Lin,et al. Sybil-proof incentive mechanisms for crowdsensing , 2017, IEEE INFOCOM 2017 - IEEE Conference on Computer Communications.
[21] Jiming Chen,et al. REAP: An Efficient Incentive Mechanism for Reconciling Aggregation Accuracy and Individual Privacy in Crowdsensing , 2017, IEEE Transactions on Information Forensics and Security.
[22] Klara Nahrstedt,et al. Theseus: Incentivizing Truth Discovery in Mobile Crowd Sensing Systems , 2017, MobiHoc.
[23] Liehuang Zhu,et al. PPMR: A Privacy-Preserving Online Medical Service Recommendation Scheme in eHealthcare System , 2019, IEEE Internet of Things Journal.
[24] Chenglin Miao,et al. A lightweight privacy-preserving truth discovery framework for mobile crowd sensing systems , 2017, IEEE INFOCOM 2017 - IEEE Conference on Computer Communications.
[25] Chenglin Miao,et al. Cloud-Enabled Privacy-Preserving Truth Discovery in Crowd Sensing Systems , 2015, SenSys.
[26] Bo Zhao,et al. Conflicts to Harmony: A Framework for Resolving Conflicts in Heterogeneous Data by Truth Discovery , 2016, IEEE Transactions on Knowledge and Data Engineering.