中国科学技术大学学报 ›› 2014, Vol. 44 ›› Issue (7): 544-553.DOI: 10.3969/j.issn.0253-2778.2014.07.002

• 论著 • 上一篇    下一篇

ARBA:基于分解重构技术的LBS隐私保护方法

林瑜,韩建民,于娟,贾泂,詹皇彬   

  1. 1.浙江师范大学数理与信息工程学院,浙江金华 321004;2.复旦大学计算机科学与技术系,上海 200433
  • 收稿日期:2014-03-21 修回日期:2014-06-15 接受日期:2014-06-15 出版日期:2023-05-11 发布日期:2014-06-15
  • 通讯作者: 韩建民
  • 作者简介:林瑜,女,1990年生,硕士. 研究方向:隐私保护. E-mail: linyu@zjnu.net
  • 基金资助:
    国家基金项目(61170108,6110019),浙江省自然科学基金(Y1100161,LQ13F020007)资助.

A novel anonymization method based on anatomy and reconstruction in LBS privacy preservation

LIN Yu, HAN Jianmin, YU Juan, JIA Jiong, ZHAN Huangbin   

  1. 1.Mathematics, Physics and Information Engineering College, Zhejiang Normal University, Jinhua 321004, China; 2.Department of Computer Science and Technology, Fudan University, Shanghai 200433, China
  • Received:2014-03-21 Revised:2014-06-15 Accepted:2014-06-15 Online:2023-05-11 Published:2014-06-15

摘要: 现有的匿名化方法多采用时空伪装技术,该技术计算负担重,LBS响应延迟时间长,导致LBS服务质量低.为此,提出了分解重构的匿名化方法,该方法首先对接收到的LBS查询集进行分组,形成满足匿名模型的等价类,然后对每个等价类根据不同的策略进行分解和重构,生成新的匿名查询集.此外,面向多种隐私需求,提出了一系列匿名模型,并进一步提出了基于分解重构技术的匿名模型的实现算法MBFAA.实验表明,提出的重构分解技术可以有效地实现各种匿名模型.

关键词: k-匿名, 位置l-多样性, 查询m-多样性, 分解重构

Abstract: Most of the existing methods are realized by temporal and spatial cloaking techniques. However, these cloaking-based methods are disadvantageous due to their high computation loads and long response delays, which lowers service quality. To address these problems, a novel technique, anatomy and reconstruction, was proposed. This technique first partitions the LBS query set into several equivalence classes, making sure that each equivalence class satisfies the given anonymity constraints. Then it reconstructs the LBS queries in each equivalence class according to the predefined strategies separately, and generates a new set of anonymous queries. Considering various privacy requirements, a series of anonymity models were proposed, and a unified anonymization algorithm MBFAA was introduced to realize these models. Experimental results show that the proposed method can effectively implement all the anonymity models.

Key words: k-anonymity, location l-diversity, query m-diversity, anatomy and reconstruction

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