基于方向控制的差分隐私轨迹数据发布方法

doi:10.12052/gdutxb.220170

摘要/Abstract

摘要： 随着差分隐私研究及其应用的不断拓展，其在轨迹数据发布的隐私保护领域应用受到了广泛关注，现有研究方法大多采用Kmeans聚类方法对轨迹进行聚类划分，但由于差分隐私约束下的轨迹数据集受到噪声的扰动，导致现有的聚类方法无法保证最后的收敛效果。本文提出了一种基于方向控制的差分隐私保护轨迹数据发布方法。首先，提出了基于SKmeans||聚类的轨迹泛化算法，在聚类迭代过程中针对质心的更新，加入方向控制机制，设计指数机制中的打分函数控制质心的收敛，保证高维数据聚类的质量。其次，设计了一个基于有界阶梯噪声机制的轨迹数据发布算法，其中的有界阶梯噪声机制保证了在隐藏轨迹点真实计数的同时，提高了发布后轨迹数据的可用性。最后，通过实验验证了本文所提出方法的有效性。

关键词: 差分隐私, 聚类, 轨迹数据发布, 方向控制, 有界噪声

Abstract: With the continuous expansion of differential privacy and its applications, its application in the privacy protection field of trajectory data release has received extensive attention. However， most existing research methods use the Kmeans to cluster the trajectory, , which cannot guarantee the final convergence due to the fact that the trajectory datasets under differential privacy constraints are usually disturbed by noise. To addrss this, this paper proposes an orientation control-based differential privacy-preserving trajectory data publishing method. Firstly, a trajectory generalization algorithm based on SKmeans|| clustering is proposed, which updates the centroid via a direction control mechanism during iterative process of clustering, and designs a scoring function in the index mechanism to control the convergence of the centroid, such that the quality of high dimensional data clustering can be improved. Secondly, a trajectory data publishing algorithm based on bounded noise mechanism is designed, which improves the availability of trajectory data after publishing. Meanwhile, the bounded noise mechanism ensures the true count of the hidden trajectory. Finally, the effectiveness of the method proposed in this paper is evaluated by experiments.

Key words: differential privacy, clustering, trajectory publishing, orientation control, bounded noise

中图分类号:

TP391

李杨, 周莹. 基于方向控制的差分隐私轨迹数据发布方法[J]. 广东工业大学学报, 2023, 40(05): 56-63.

Li Yang, Zhou Ying. Differential Privacy Trajectory Data Publishing Based on Orientation Control[J]. Journal of Guangdong University of Technology, 2023, 40(05): 56-63.

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