A trajectory data publishing algorithm satisfying local suppression
Suppressing the trajectory data to be released can effectively reduce the risk of user privacy leakage. However, the global suppression of the data set to meet the traditional privacy model method reduces the availability of trajectory data. Therefore, we propose a trajectory data differential priva...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-02-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147721993402 |
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| _version_ | 1849695787870584832 |
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| author | Xiaohui Li Yuliang Bai Yajun Wang Bo Li |
| author_facet | Xiaohui Li Yuliang Bai Yajun Wang Bo Li |
| author_sort | Xiaohui Li |
| collection | DOAJ |
| description | Suppressing the trajectory data to be released can effectively reduce the risk of user privacy leakage. However, the global suppression of the data set to meet the traditional privacy model method reduces the availability of trajectory data. Therefore, we propose a trajectory data differential privacy protection algorithm based on local suppression Trajectory privacy protection based on local suppression (TPLS) to provide the user with the ability and flexibility of protecting data through local suppression. The main contributions of this article include as follows: (1) introducing privacy protection method in trajectory data release, (2) performing effective local suppression judgment on the points in the minimum violation sequence of the trajectory data set, and (3) proposing a differential privacy protection algorithm based on local suppression. In the algorithm, we achieve the purpose Maximal frequent sequence (MFS) sequence loss rate in the trajectory data set by effective local inhibition judgment and updating the minimum violation sequence set, and then establish a classification tree and add noise to the leaf nodes to improve the security of the data to be published. Simulation results show that the proposed algorithm is effective, which can reduce the data loss rate and improve data availability while reducing the risk of user privacy leakage. |
| format | Article |
| id | doaj-art-cdea272a2f6741dd9a82d520235ae76a |
| institution | DOAJ |
| issn | 1550-1477 |
| language | English |
| publishDate | 2021-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-cdea272a2f6741dd9a82d520235ae76a2025-08-20T03:19:39ZengWileyInternational Journal of Distributed Sensor Networks1550-14772021-02-011710.1177/1550147721993402A trajectory data publishing algorithm satisfying local suppressionXiaohui LiYuliang BaiYajun WangBo LiSuppressing the trajectory data to be released can effectively reduce the risk of user privacy leakage. However, the global suppression of the data set to meet the traditional privacy model method reduces the availability of trajectory data. Therefore, we propose a trajectory data differential privacy protection algorithm based on local suppression Trajectory privacy protection based on local suppression (TPLS) to provide the user with the ability and flexibility of protecting data through local suppression. The main contributions of this article include as follows: (1) introducing privacy protection method in trajectory data release, (2) performing effective local suppression judgment on the points in the minimum violation sequence of the trajectory data set, and (3) proposing a differential privacy protection algorithm based on local suppression. In the algorithm, we achieve the purpose Maximal frequent sequence (MFS) sequence loss rate in the trajectory data set by effective local inhibition judgment and updating the minimum violation sequence set, and then establish a classification tree and add noise to the leaf nodes to improve the security of the data to be published. Simulation results show that the proposed algorithm is effective, which can reduce the data loss rate and improve data availability while reducing the risk of user privacy leakage.https://doi.org/10.1177/1550147721993402 |
| spellingShingle | Xiaohui Li Yuliang Bai Yajun Wang Bo Li A trajectory data publishing algorithm satisfying local suppression International Journal of Distributed Sensor Networks |
| title | A trajectory data publishing algorithm satisfying local suppression |
| title_full | A trajectory data publishing algorithm satisfying local suppression |
| title_fullStr | A trajectory data publishing algorithm satisfying local suppression |
| title_full_unstemmed | A trajectory data publishing algorithm satisfying local suppression |
| title_short | A trajectory data publishing algorithm satisfying local suppression |
| title_sort | trajectory data publishing algorithm satisfying local suppression |
| url | https://doi.org/10.1177/1550147721993402 |
| work_keys_str_mv | AT xiaohuili atrajectorydatapublishingalgorithmsatisfyinglocalsuppression AT yuliangbai atrajectorydatapublishingalgorithmsatisfyinglocalsuppression AT yajunwang atrajectorydatapublishingalgorithmsatisfyinglocalsuppression AT boli atrajectorydatapublishingalgorithmsatisfyinglocalsuppression AT xiaohuili trajectorydatapublishingalgorithmsatisfyinglocalsuppression AT yuliangbai trajectorydatapublishingalgorithmsatisfyinglocalsuppression AT yajunwang trajectorydatapublishingalgorithmsatisfyinglocalsuppression AT boli trajectorydatapublishingalgorithmsatisfyinglocalsuppression |