个人信息Personal Information
教授
博士生导师
硕士生导师
主要任职:软件学院、大连理工大学-立命馆大学国际信息与软件学院副院长
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:软件学院、国际信息与软件学院
学科:软件工程. 计算机应用技术
联系方式:guocheng@dlut.edu.cn
电子邮箱:guocheng@dlut.edu.cn
Dynamic Data Integrity Auditing Method Supporting Privacy Protection in Vehicular Cloud Environment
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论文类型:期刊论文
发表时间:2018-01-01
发表刊物:IEEE ACCESS
收录刊物:SCIE
卷号:6
页面范围:43785-43797
ISSN号:2169-3536
关键字:Cloud storage; VANETs; data integrity auditing; dynamic updating; privacy protection
摘要:The advantages of cloud storage make more and more tenants outsource their data to the cloud. In the vehicular ad hoc networks, the sensors on the vehicle can collect road information being available for analyzing traffic conditions and their integrity must be guaranteed. Due to the limited storage capability, the vehicles tend to store the valid information have been collected on the cloud servers. However, unlike using local storage devices, the vehicles no longer have absolute control over the cloud data. Clearly, as the tenants of the cloud storage, the vehicles are most concerned about the data integrity. It is a pity that many existing integrity auditing schemes have some shortcomings, such as low efficiency in data dynamic updating, leakage of data privacy, and high auditing cost. To solve these problems, this paper proposes a dynamic data integrity auditing scheme supporting data privacy protection. First, build the hierarchical multiple branches tree data authentication structure in the initialization phase. Second, design a data integrity auditing scheme based on the bilinear pairing mapping technology and the Boneh-Lynn-Shacham digital signature mechanism, and describe the process of data dynamic updating in detail. Finally, security analysis and performance analysis are carried out in the evaluation of the scheme. The security analysis shows that the scheme can satisfy auditing correctness, support data privacy protection, resist forgery attack, and replay attack. The performance analysis shows that, compared with the existing scheme, the scheme reduces the time cost of data integrity auditing and dynamic updating.