基于差分隐私的活动模式保护与时空轨迹发布方法

doi:10.12263/DZXB.20210631

电子学报 ›› 2023, Vol. 51 ›› Issue (3): 552-563.DOI: 10.12263/DZXB.20210631

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

重庆大学计算机学院，重庆 400044

收稿日期:2021-05-18 修回日期:2022-04-16 出版日期:2023-03-25
- 通讯作者:
- 汪成亮
- 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
- 基金资助:
- 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)

Differentially Private Activity Pattern and Spatial-Temporal Trajectory Publication

ZENG Zhuo, WANG Cheng-liang, MA Fei

Computer School，Chongqing University，Chongqing 400044，China

Received:2021-05-18 Revised:2022-04-16 Online:2023-03-25 Published:2023-04-20
- Corresponding author:
- WANG Cheng-liang
- Supported by:
- National Natural Science Foundation of China(61672115);Chongqing Technology Innovation & Application Development Key Project(cstc2020jscx-dxwtBX0055)

摘要/Abstract

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.

关键词: 活动模式, 群体差分隐私, 时空轨迹, 动静态信息

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.

Key words: activity pattern, group differential privacy, spatial-temporal trajectories, dynamic and static information

中图分类号:

TP309.2

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(3): 552-563.

Zhuo ZENG, Cheng-liang WANG, Fei MA . Differentially Private Activity Pattern and Spatial-Temporal Trajectory Publication[J]. Acta Electronica Sinica, 2023, 51(3): 552-563.

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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

Differentially Private Activity Pattern and Spatial-Temporal Trajectory Publication

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