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SCIENCE CHINA Information Sciences, Volume 62, Issue 3: 039106(2019) https://doi.org/10.1007/s11432-018-9483-x

UMBRELLA: user demand privacy preserving framework based on association rules and differential privacy in social networks

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  • ReceivedApr 10, 2018
  • AcceptedJun 8, 2018
  • PublishedOct 18, 2018

Abstract

There is no abstract available for this article.


Acknowledgment

This work was supported by National Natural Sciences Foundation of China (Grant No. 61501211), Basic Research Project of Shenzhen (Grant Nos. JCYJ20160531192013063, JCYJ20170307151148585), Natural Sciences Foundation of Guangdong (Grant No. 2017A030313372), Natural Scientific Research Innovation Foundation in Harbin Institute of Technology, Natural Sciences Foundation of Jiangxi (Grant Nos. 20151BAB217001, 20151BAB217018), and ST Foundation of Jingdezhen.


References

[1] Li H X, Zhu H J, Ma D. Demographic information inference through meta-data analysis of wi-fi traffic. IEEE Trans Mobile Comput, 2018, 17: 1033-1047 CrossRef Google Scholar

[2] Li H X, Chen Q R, Zhu H J, et al. Privacy leakage via de-anonymization and aggregation in heterogeneous social networks. IEEE Trans Depen Secur Comput, 2017. doi: 10.1109/TDSC.2017.2754249. Google Scholar

[3] Peng T, Liu Q, Wang G J. Enhanced location privacy preserving scheme in location-based services. IEEE Syst J, 2017, 11: 219-230 CrossRef ADS Google Scholar

[4] Shahid A R, Jeukeng L, Zeng W, et al. PPVC: privacy preserving voronoi cell for location-based services. In: Proceedings of International Conference on Computing, Networking and Communications, Santa Clara, 2017. 351--355. Google Scholar

[5] Ma X D, Li H, Ma J F. APPLET: a privacy-preserving framework for location-aware recommender system. Sci China Inf Sci, 2017, 60: 092101 CrossRef Google Scholar

[6] Zhu H, Lu R X, Huang C. An efficient privacy-preserving location-based services query scheme in outsourced cloud. IEEE Trans Veh Technol, 2016, 65: 7729-7739 CrossRef Google Scholar

[7] Andrés M E, Bordenabe N E, Chatzikokolakis K, et al. Geo-indistinguishability: differential privacy for location-based systems. In: Proceedings of the 2013 ACM SIGSAC Conference on Computer and Communications Security, Berlin, 2013. 901--914. Google Scholar

[8] Shokri R. Privacy games: optimal user-centric data obfuscation. In: Proceedings of the 15th Privacy Enhancing Technologies, Philadelphia, 2015. 299--315. Google Scholar

[9] Feng L, Dillon T, Liu J. Inter-transactional association rules for multi-dimensional contexts for prediction and their application to studying meteorological data. Data Knowl Eng, 2001, 37: 85-115 CrossRef Google Scholar

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