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西安电子科技大学网络与信息安全学院,陕西 西安 710071
[ "张文静(1988- ),女,黑龙江绥化人,西安电子科技大学博士生,主要研究方向为数据隐私和隐私度量" ]
[ "刘樵(1989- ),男,陕西咸阳人,博士,西安电子科技大学讲师,主要研究方向为物理层安全" ]
[ "朱辉(1981- ),男,河南周口人,博士,西安电子科技大学教授、博士生导师,主要研究方向为数据安全与隐私保护、安全方案及协议设计、网络及应用安全" ]
网络出版日期:2019-12,
纸质出版日期:2019-12-25
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张文静, 刘樵, 朱辉. 基于信息论方法的多等级位置隐私度量与保护[J]. 通信学报, 2019,40(12):51-59.
Wenjing ZHANG, Qiao LIU, Hui ZHU. Evaluation and protection of multi-level location privacy based on an information theoretic approach[J]. Journal on communications, 2019, 40(12): 51-59.
张文静, 刘樵, 朱辉. 基于信息论方法的多等级位置隐私度量与保护[J]. 通信学报, 2019,40(12):51-59. DOI: 10.11959/j.issn.1000-436x.2019235.
Wenjing ZHANG, Qiao LIU, Hui ZHU. Evaluation and protection of multi-level location privacy based on an information theoretic approach[J]. Journal on communications, 2019, 40(12): 51-59. DOI: 10.11959/j.issn.1000-436x.2019235.
针对位置数据拥有者对数据使用者具有不同的信任程度时,会对使用者进行不同等级的划分并向其发布不同扰动程度的位置数据这一场景中的隐私泄露问题,提出了基于信息论中的互信息的隐私度量方法与保护问题。此外,基于互信息提出了度量攻击者获取不同等级的扰动数据而对真实位置数据进行更精确的推断分析所造成的隐私泄露的方法。借鉴用于求解率失真函数的Blahut-Arimoto算法提出了多等级位置隐私保护机制。实验结果表明,在上述2种问题场景中,所提位置隐私保护机制与基于差分隐私的位置隐私保护方法相比具有更低的隐私泄露,且当真实位置数据具有显著不同的受欢迎程度时,优势更明显。
A privacy metric based on mutual information was proposed to measure the privacy leakage occurred when location data owner trust data users at different levels and need to publish the distorted location data to each user according to her trust level
based on which an location privacy protection mechanism (LPPM)was generated to protect user’s location privacy.In addition
based on mutual information
a metric was proposed to measure the privacy leakage caused by attackers obtaining different levels of distorted location data and then performing inference attack on the original location data more accurately.Another privacy metric was also proposed to quantify the information leakage occurred in the scenario based on mutual information.In particular
the proposed privacy mechanism was designed by modifying Blahut-Arimoto algorithm in rate-distortion theory.Experimental results show the superiority of the proposed LPPM over an existing LPPM in terms of location privacyutility tradeoff in both scenarios
which is more conspicuous when there are highly popular locations.
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