Privacy level evaluation of differential privacy for time series based on filtering theory
Academic communication|更新时间:2024-06-05
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Privacy level evaluation of differential privacy for time series based on filtering theory
Journal on CommunicationsVol. 38, Issue 5, Pages: 172-181(2017)
作者机构:
1. 武汉大学测绘遥感信息工程国家重点实验室,湖北 武汉 430079
2. 武汉大学地球空间信息技术协同创新中心,湖北 武汉 430079
作者简介:
基金信息:
The National Natural Science Foundation of China(41671443);The National Natural Science Foundation of China(41371402);The Applied Basic Research Program of Wuhan(2016010101010024)
Wen-jun XIONG, Zheng-quan XU, Hao WANG. Privacy level evaluation of differential privacy for time series based on filtering theory[J]. Journal on Communications, 2017, 38(5): 172-181.
DOI:
Wen-jun XIONG, Zheng-quan XU, Hao WANG. Privacy level evaluation of differential privacy for time series based on filtering theory[J]. Journal on Communications, 2017, 38(5): 172-181. DOI: 10.11959/j.issn.1000-436x.2017110.
Privacy level evaluation of differential privacy for time series based on filtering theory
The current differential privacy preserving methods on correlated time series were not designed by protecting against a specific attack model
and the privacy level of them couldn’t be measured.Therefore
an attack model was put forward to solve the above problems.Since the noise series added by these methods was independent and identically distributed
and the time series could be seen as a short-time stationary process
a linear filter was designed based on filtering theory
in order to filter out the noise series.Experimental results show that the proposed attack model is valid
and can work as a unified measurement for these methods.
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references
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