Differential Privacy Preservation for Continuous Release of Real-Time Location Data
Continuous real-time location data is very important in the big data era, but the privacy issues involved is also a considerable topic. It is not only necessary to protect the location privacy at each release moment, but also have to consider the impact of data correlation. Correlated Laplace Mechan...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/26/2/138 |
| _version_ | 1827343673752289280 |
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| author | Lihui Mao Zhengquan Xu |
| author_facet | Lihui Mao Zhengquan Xu |
| author_sort | Lihui Mao |
| collection | DOAJ |
| description | Continuous real-time location data is very important in the big data era, but the privacy issues involved is also a considerable topic. It is not only necessary to protect the location privacy at each release moment, but also have to consider the impact of data correlation. Correlated Laplace Mechanism (CLM) is a sophisticated method to implement differential privacy on correlated time series. This paper aims to solve the key problems of applying CLM in continuous location release. Based on the finding that the location increment is approximately stationary in many scenarios, a location correlation estimation method based on the location increment is proposed to solve the problem of nonstationary location data correlation estimation; an adaptive adjustment model for the CLM filter based on parameter quantization idea (QCLM) as well as its effective implementation named QCLM-Lowpass utilizing the lowpass spectral characteristics of location data series is proposed to solve the problem of output deviations due to the undesired transient response of the CLM filter in time-varying environments. Extensive simulations and real data experiments validate the effectiveness of the proposed approach and show that the privacy scheme based on QCLM-Lowpass can offer a better balance between the ability to resist correlation-based attacks and data availability. |
| first_indexed | 2024-03-07T22:33:42Z |
| format | Article |
| id | doaj.art-8b8e414050424273b57211bb572d73c2 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-07T22:33:42Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-8b8e414050424273b57211bb572d73c22024-02-23T15:15:42ZengMDPI AGEntropy1099-43002024-02-0126213810.3390/e26020138Differential Privacy Preservation for Continuous Release of Real-Time Location DataLihui Mao0Zhengquan Xu1State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaContinuous real-time location data is very important in the big data era, but the privacy issues involved is also a considerable topic. It is not only necessary to protect the location privacy at each release moment, but also have to consider the impact of data correlation. Correlated Laplace Mechanism (CLM) is a sophisticated method to implement differential privacy on correlated time series. This paper aims to solve the key problems of applying CLM in continuous location release. Based on the finding that the location increment is approximately stationary in many scenarios, a location correlation estimation method based on the location increment is proposed to solve the problem of nonstationary location data correlation estimation; an adaptive adjustment model for the CLM filter based on parameter quantization idea (QCLM) as well as its effective implementation named QCLM-Lowpass utilizing the lowpass spectral characteristics of location data series is proposed to solve the problem of output deviations due to the undesired transient response of the CLM filter in time-varying environments. Extensive simulations and real data experiments validate the effectiveness of the proposed approach and show that the privacy scheme based on QCLM-Lowpass can offer a better balance between the ability to resist correlation-based attacks and data availability.https://www.mdpi.com/1099-4300/26/2/138location privacy preservation mechanismdifferential privacygeo indistinguishabilityseries indistinguishabilityCorrelated Laplace Mechanism |
| spellingShingle | Lihui Mao Zhengquan Xu Differential Privacy Preservation for Continuous Release of Real-Time Location Data Entropy location privacy preservation mechanism differential privacy geo indistinguishability series indistinguishability Correlated Laplace Mechanism |
| title | Differential Privacy Preservation for Continuous Release of Real-Time Location Data |
| title_full | Differential Privacy Preservation for Continuous Release of Real-Time Location Data |
| title_fullStr | Differential Privacy Preservation for Continuous Release of Real-Time Location Data |
| title_full_unstemmed | Differential Privacy Preservation for Continuous Release of Real-Time Location Data |
| title_short | Differential Privacy Preservation for Continuous Release of Real-Time Location Data |
| title_sort | differential privacy preservation for continuous release of real time location data |
| topic | location privacy preservation mechanism differential privacy geo indistinguishability series indistinguishability Correlated Laplace Mechanism |
| url | https://www.mdpi.com/1099-4300/26/2/138 |
| work_keys_str_mv | AT lihuimao differentialprivacypreservationforcontinuousreleaseofrealtimelocationdata AT zhengquanxu differentialprivacypreservationforcontinuousreleaseofrealtimelocationdata |