基于联合熵隐私保护的自适应动态Mix-zone方案

冯霞; 刘亚伟

doi:10.11959/j.issn.1000-436x.2018038

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基于联合熵隐私保护的自适应动态Mix-zone方案

论文Ⅰ：物联网与安全 | 更新时间：2024-06-05

- 基于联合熵隐私保护的自适应动态Mix-zone方案
- Dynamic Mix-zone scheme with joint-entropy based metric for privacy-perserving in IoV
- 通信学报 2018年39卷第3期页码：76-85
- 作者机构：
  
  1. 江苏大学汽车与交通工程学院，江苏镇江 212013
  2. 江苏省工业网络安全技术重点实验室，江苏镇江 212013
  3. 安徽大学计算机科学与技术学院，安徽合肥 230601
- 作者简介：
  
  [ "冯霞（1983-），女，江苏镇江人，博士，江苏大学讲师，主要研究方向为车联网安全。" ]
  [ "刘亚伟（1994-），男，安徽阜阳人，安徽大学硕士生，主要研究方向为车联网安全、云计算等。" ]
- 基金信息：
  
  国家自然科学基金资助项目(U1736216);国家自然科学基金资助项目(61472001);国家自然科学基金资助项目(61702233);江苏省重点研发计划基金资助项目(BE2015136)
- DOI：10.11959/j.issn.1000-436x.2018038
  中图分类号： TP391
- 网络出版日期：2018-03，
  
  纸质出版日期：2018-03-25
- 稿件说明：
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冯霞, 刘亚伟. 基于联合熵隐私保护的自适应动态Mix-zone方案[J]. 通信学报, 2018,39(3):76-85.

Xia FENG, Yawei LIU. Dynamic Mix-zone scheme with joint-entropy based metric for privacy-perserving in IoV[J]. Journal on communications, 2018, 39(3): 76-85.
冯霞, 刘亚伟. 基于联合熵隐私保护的自适应动态Mix-zone方案[J]. 通信学报, 2018,39(3):76-85. DOI： 10.11959/j.issn.1000-436x.2018038.

Xia FENG, Yawei LIU. Dynamic Mix-zone scheme with joint-entropy based metric for privacy-perserving in IoV[J]. Journal on communications, 2018, 39(3): 76-85. DOI： 10.11959/j.issn.1000-436x.2018038.

摘要

针对车联网中 Mix-zone 方案灵活性低以及隐私保护程度对用户缺乏透明度的问题，提出一种交通自适应的动态Mix-zone创建方法，可以根据道路交通状况为车辆动态创建Mix-zone，随时随地为车辆创建Mix-zone进行假名更换，建立基于身份和位置的隐私保护；提出对 Mix-zone 进行隐私分级的联合熵度量模型，可通过归一化的定量计算结果度量 Mix-zone 达到当前区域车辆隐私需求的程度。使用深圳市某区的出租车辆的轨迹数据验证了联合熵隐私度量模型及基于该模型的 Mix-zone 创建方案，实验结果表明，该联合熵模型能刻画交通场景中参数与隐私保护程度的正比关系，在联合熵所表示的无序性指标上，所提 Mix-zone 创建方案相较其他方案，具有更好的隐私保护效果。

Abstract

Aiming at the weak flexibility and lack of users’ transparency existing in the current Mix-zone schemes for Internet of vehicle (IoV)

a dynamic was proposed for Mix-zone construction with traffic adaption

which could construct a Mix-zone for the vehicles dynamically according to the traffic conditions for changing pseudonym at anytime and anywhere.This kind of Mix-zone could achieve privacy-preserving based on the identity and location.In addition

a novel traffic-adaptive metric was presented for classifying the privacy leveled in Mix-zone

which applied the normalization quantitation to measure the degree of Mix-zone’s privacy demanding by the current region.It was verified that the joint entropy-based privacy measuring model and the Mix-zone construction scheme by utilizing the trajectory data of taxis in certain district in Shenzhen city.The experimental shows that the proposed combination entropy-based model could depict the proportional relationship between the traffic scene parameters and the privacy-preserving degrees.The scheme is better in performance over the related methods

and strikes a good balance between location privacy and service usability.

关键词

Keywords

references

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