基于差分隐私的活动模式保护与时空轨迹发布方法

曾卓; 汪成亮; 马飞

doi:10.12263/DZXB.20210631

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基于差分隐私的活动模式保护与时空轨迹发布方法

学术论文 | 更新时间：2025-12-08

- 基于差分隐私的活动模式保护与时空轨迹发布方法
- Differentially Private Activity Pattern and Spatial-Temporal Trajectory Publication
- 电子学报 2023年51卷第3期页码：552-563
- 作者机构：
  
  重庆大学计算机学院，重庆 400044
- 作者简介：
  
  [ "曾卓男，1991年5月出生，重庆涪陵人.重庆大学博士生，主要研究轨迹隐私保护，动态图神经网络安全等.E-mail: zengz@ cqu.edu.cn" ]
  [ "汪成亮（通讯作者）男，1975年5月出生，四川资阳人.博士，现为重庆大学计算机学院教授，博士生导师.主要研究领域为复杂系统智能控制，无线网络及RFID研究与应用等." ]
  [ "马飞男，1993年4月出生，河南商丘人.重庆大学博士生，主要研究方向为语音信号处理、迁移学习.E-mail: mafei@cqu.edu.cn" ]
- 基金信息：
  
  国家自然科学基金(61672115);重庆市技术创新与应用发展专项重大主题专项(cstc2020jscx-dxwtBX0055)
- DOI：10.12263/DZXB.20210631
  中图分类号： TP309.2
- 收稿：2021-05-18，
  
  修回：2022-04-16，
  
  纸质出版：2023-03-25
- 稿件说明：
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曾卓,汪成亮,马飞.基于差分隐私的活动模式保护与时空轨迹发布方法[J].电子学报,2023,51(03):552-563.

ZENG Zhuo,WANG Cheng-liang,MA Fei.Differentially Private Activity Pattern and Spatial-Temporal Trajectory Publication[J].ACTA ELECTRONICA SINICA,2023,51(03):552-563.
曾卓,汪成亮,马飞.基于差分隐私的活动模式保护与时空轨迹发布方法[J].电子学报,2023,51(03):552-563. DOI： 10.12263/DZXB.20210631.

ZENG Zhuo,WANG Cheng-liang,MA Fei.Differentially Private Activity Pattern and Spatial-Temporal Trajectory Publication[J].ACTA ELECTRONICA SINICA,2023,51(03):552-563. DOI： 10.12263/DZXB.20210631.

摘要

为了解决用户轨迹数据发布时的活动模式泄露问题，本文提出了一种基于差分隐私的活动模式保护与时空数据发布方法DPAP-STTP（Differentially Private Activity Pattern and Spatial-Temporal Trajectory Publication），该方法即保护了用户时空数据中活动模式的隐私，又可以保证所发布时空轨迹在服务建议生成上的有效性.在DPAP-STTP中，用户的活动模式表示为个人代表性轨迹的动静态信息，包括代表性轨迹的时空密度分布、时空路径分布、移动模式以及时空跨度.另外，DPAP-STTP通过隐私保护预算与隐私保护阈值对该动静态信息进行调控，然后根据调控后的动静态信息依次划分时空网格、重构轨迹所处时空区间、时空轨迹点随机采样，最终生成满足群体差分隐私的时空轨迹进行发布.本文的实验比较了DPAP-STTP与DP-STAR（Differential Private Synthetic Trajectory Publisher）、BNA（Bounded Noise-Adding）所生成的轨迹在特定时空范围内的有效性，证明DPAP-STTP不但可重构服从群体差分隐私的时空轨迹，而且在时空网格上维持了时空轨迹的有效性.

Abstract

In order to solve activity pattern leakage problems while user trajectory data publishing

the paper proposes the DPAP-STTP (Differentially Private Activity Pattern and Spatial-Temporal Trajectory Publication) method to publish spatial-temporal trajectories for achieving required services suggestions in support of users while preserving the privacy of activity patterns. In DPAP-STTP

users' activity patterns are represented as dynamic and static information of personal representative trajectories

including spatial-temporal density distribution

spatial-temporal trip distribution

mobility pattern and spatial-temporal span. Additionally

according to allocated privacy budget and specific privacy-preserving threshold

DPAP-STTP preserves the privacy of dynamic and static information

and uses perturbed information to divide spatial-temporal grids

reconstruct spatial-temporal passing grids

randomly select spatial-temporal point

and finally generate spatial-temporal trajectories with group differential privacy satisfied. The experiment in this paper compares the DPAP-STTP with DP-STAR (Differential Private Synthetic Trajectory Publisher) and BNA (Bounded Noise-Adding) for presenting the utility of DPAP-STTP trajectories. Consequently

the DPAP-STTP method is proved to generate spatial-temporal trajectories which follow the group differential privacy and maintain their utility in some spatial-temporal scopes.

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references

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