Uncertain trajectory privacy-preserving method of moving object

Shuang WANG; Fu-cai ZHOU; Li-na WU

doi:10.11959/j.issn.1000-436x.2015286

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Uncertain trajectory privacy-preserving method of moving object

Academic paper | 更新时间：2024-06-05

- Uncertain trajectory privacy-preserving method of moving object
- Journal on Communications Vol. 36, Issue Z1, Pages: 94-102(2015)
- 作者机构：
  
  东北大学软件学院，辽宁沈阳 110169
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61440014);The National Natural Science Foundation of China(61300196);The Fundamental Research Funds for the Central Universities(130317003)
- DOI：10.11959/j.issn.1000-436x.2015286
  CLC： TP309.7
- Online First：2015-11，
  
  Published：25 November 2015
- 稿件说明：
移动端阅览
Shuang WANG, Fu-cai ZHOU, Li-na WU. Uncertain trajectory privacy-preserving method of moving object[J]. Journal on Communications, 2015, 36(Z1): 94-102.
DOI：

Shuang WANG, Fu-cai ZHOU, Li-na WU. Uncertain trajectory privacy-preserving method of moving object[J]. Journal on Communications, 2015, 36(Z1): 94-102. DOI： 10.11959/j.issn.1000-436x.2015286.

摘要

随着移动设备和定位技术的发展，产生了大量的移动对象轨迹数据，相伴而来的是个人隐私泄露问题。现有的轨迹隐私保护研究均假设轨迹数据是准确无误的，但由于数据采集设备不精确、移动对象延迟更新等原因，轨迹数据不确定性普遍存在。提出了一种基于K-匿名的不确定轨迹数据隐私保护方法，对发布的数据进行隐私处理，该方法首次将线性轨迹转化为不确定区域的思想引进轨迹数据的隐私处理。首先，使用概率统计的方法将轨迹泛化成一个更为真实的轨迹区域，然后将相似度高的轨迹域聚合成等价类进行数据的隐匿和发布，最后在真实的数据集上进行实验。

Abstract

With the development of location based service(LBS) and location-aware devices，the amount of trajectories of moving objects collected by service providers was continuously increasing

meanwhile

it can cause great threaten for personal privacy.Most researches of trajectory privacy preserving were on deterministic data

however

trajectory’s uncertainty was inherent due to the inaccuracy of data acquisition equipment

delayed update

and so on.A new method was prosed to protect the privacy of trajectory data in publishing.It is the first time to present the idea that transforming the trajectory to an uncertain area to cluster.First

a probability statistics method to model the trajectory to an uncertain area was proposed.Second

the similar uncertain area into a cluster was put and sanitized in an equivalence class.Finally

the performance of the proposal was compared with (K δ)-anonymity model in real datasets.

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references

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