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

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Acknowledgements

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 S&T Foundation of Jingdezhen.

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Authors and Affiliations

  1. Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China

    Chunliu Yan, Ziyi Ni, Bin Cao, Shaohua Wu & Qinyu Zhang

  2. Faculty of Computer Science, University of New Brunswick, Fredericton, E3B 5A3, Canada

    Rongxing Lu

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  1. Chunliu Yan
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  2. Ziyi Ni
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  3. Bin Cao
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  4. Rongxing Lu
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  5. Shaohua Wu
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  6. Qinyu Zhang
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Correspondence to Bin Cao.

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Yan, C., Ni, Z., Cao, B. et al. UMBRELLA: user demand privacy preserving framework based on association rules and differential privacy in social networks. Sci. China Inf. Sci. 62, 39106 (2019). https://doi.org/10.1007/s11432-018-9483-x

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