• 其他栏目

    宁兆龙

    • 副教授     硕士生导师
    • 主要任职:无
    • 性别:男
    • 毕业院校:东北大学
    • 学位:博士
    • 在职信息:在职
    • 所在单位:软件学院
    • 学科:软件工程 通信与信息系统
    • 联系方式:zhaolongning@dlut.edu.cn
    • 电子邮箱:

    访问量:

    开通时间 :..

    最后更新时间:..

    A Privacy-Preserving Message Forwarding Framework for Opportunistic Cloud of Things

    点击量:

    论文类型:期刊论文

    第一作者:Wang, Xiaojie

    合写作者:Ning, Zhaolong,Zhou, MengChu,Hu, Xiping,Wang, Lei,Hu, Bin,Kwok, Ricky Y. K.,Guo, Yi

    发表时间:2018-12-01

    发表刊物:IEEE INTERNET OF THINGS JOURNAL

    收录刊物:SCIE、Scopus

    卷号:5

    期号:6

    页面范围:5281-5295

    ISSN号:2327-4662

    关键字:Cloud of Things (CoT); individual privacy; message forwarding; mobility prediction; opportunistic networking

    摘要:As an emerging communication platform, opportunistic Cloud of Things (CoT) is promising for clients to exchange messages through opportunistic contacts in cloud computing-enabled Internet of Things. Recently, numerous socially aware schemes have been put forward, leveraging users' social attributes and contact history to predict future contacts with the purpose of improving message forwarding efficiency and network throughput. However, individual privacy is generally overlooked in the prediction process and transmission stage of opportunistic CoT. In this paper, we construct a privacy-preserving message forwarding framework for opportunistic CoT to guarantee individual privacy and improve transmission efficiency. We first set up a two-layer architecture of a cloud server to improve communication efficiency for terminal clients. By integrating a security-based mobility prediction algorithm with a routing decision process, our scheme can effectively protect individual privacy. We integrate an attribute-based cryptographic algorithm with a message delivery process to enable our scheme to resist attacks, such as Sybil attack, drop for profit, and data tampered attack. Compared with some existing solutions, our scheme improves network security significantly at the cost of slightly increased communication overhead.