Journal of Computer Applications ›› 2024, Vol. 44 ›› Issue (2): 496-503.DOI: 10.11772/j.issn.1001-9081.2023030259

• Cyber security • Previous Articles    

Interference trajectory publication based on improved glowworm swarm algorithm and differential privacy

Peng PENG1,2,3, Zhiwei NI1,3(), Xuhui ZHU1,3, Qian CHEN1,3   

  1. 1.School of Management,Hefei University of Technology,Hefei Anhui 230009,China
    2.School of Business,North Minzu University,Yinchuan Ningxia 750021,China
    3.Key Laboratory of Process Optimization and Intelligent Decision?making,Ministry of Education(Hefei University of Technology),Hefei Anhui 230009,China
  • Received:2023-03-14 Revised:2023-06-03 Accepted:2023-06-27 Online:2023-09-01 Published:2024-02-10
  • Contact: Zhiwei NI
  • About author:PENG Peng, born in 1988, Ph. D. candidate, lecturer. His research interests include intelligent optimization, spatial crowdsourcing.
    ZHU Xuhui, born in 1991, Ph. D., lecturer. His research interests include deep learning, intelligent computing.
    CHEN Qian, born in 1991, Ph. D. candidate. His research interests include data security, privacy computing.
  • Supported by:
    National Natural Science Foundation of China(71901001);Anhui Provincial Natural Science Foundation(1908085QG298)


彭鹏1,2,3, 倪志伟1,3(), 朱旭辉1,3, 陈千1,3   

  1. 1.合肥工业大学 管理学院,合肥 230009
    2.北方民族大学 商学院,银川 750021
    3.过程优化与智能决策教育部重点实验室(合肥工业大学),合肥 230009
  • 通讯作者: 倪志伟
  • 作者简介:彭鹏(1988—),男,安徽巢湖人,讲师,博士研究生,CCF会员,主要研究方向:智能优化、空间众包
  • 基金资助:


In view of the redundancy of dataset and the risk of privacy leakage caused by the similarity of track shape when the interference track was noised and publicated by the historical track, an IGSO-SDTP (Trajectory Protection of Simplification and Differential privacy of the track data based on Improved Glowworm Swarm Optimization) was proposed. Firstly, the historical trajectory dataset was reduced based on the position salient points. Secondly, the simplified trajectory dataset was generalized and noised by combining k-anonymity and differential privacy. Finally, a weighted distance was designed to take into account the distance error and track similarity, and the weighted distance was used as the evaluation index to solve the interference track with a small weighted distance based on IGSO (Improved Glowworm Swarm Optimization) algorithm. Experimental results on multiple datasets show that compared with the RD(Differential privacy for Raw trajectory data), SDTP(Trajectory Protection of Simplification and Differential privacy), LIC(Linear Index Clustering algorithm), and DPKTS(Differential Privacy based on K-means Trajectory shape Similarity), the weighted distances obtained by IGSO-SDTP are reduced by 21.94%, 9,15%, 14.25% and 10.55%, respectively. It can be seen that the interference trajectory publicated by IGSO-SDTP has better usability and stability.

Key words: interference trajectory, differential privacy, Improved Glowworm Swarm Optimization (IGSO) algorithm, weighted distance, salient point judgment


针对历史轨迹加噪发布干扰轨迹时数据集的冗余问题和轨迹形状相似带来的隐私泄露风险,提出轨迹数据先约简后泛化再进行差分隐私加噪的基于改进萤火虫群优化求解的干扰轨迹发布保护机制(IGSO-SDTP)。首先,基于位置显著点约简历史轨迹数据集;其次,结合k?匿名和差分隐私对简化后的轨迹数据集分别进行泛化和加噪;最后,设计了兼顾距离误差和轨迹相似性的加权距离,并以加权距离为评价指标,基于改进萤火虫群优化(IGSO)算法求解加权距离小的干扰轨迹。在多个数据集上的实验结果表明,与RD(Differential privacy for Raw trajectory data)、SDTP(Trajectory Protection of Simplification and Differential privacy)、LIC(Linear Index Clustering algorithm)、DPKTS(Differential Privacy based on K-means Trajectory shape Similarity)相比,IGSO-SDTP方法得到的加权距离分别降低了21.94%、9.15%、14.25%、10.55%,说明所提方法发布的干扰轨迹可用性和稳定性更好。

关键词: 干扰轨迹, 差分隐私, 改进萤火虫群优化算法, 加权距离, 显著点判断

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