计算机应用 ›› 2014, Vol. 34 ›› Issue (4): 994-998.DOI: 10.11772/j.issn.1001-9081.2014.04.0994

• 先进计算 • 上一篇    下一篇

面向个性化云服务基于用户类型和隐私保护的信任模型

刘飞1,2,3,罗永龙2,3,郭良敏2,3,马苑2,3   

  1. 1.
    2. 安徽师范大学 数学计算机科学学院,安徽 芜湖 241003;
    3. 安徽师范大学 网络与信息安全工程技术研究中心,安徽 芜湖 241003
  • 收稿日期:2013-10-17 修回日期:2013-12-12 出版日期:2014-04-01 发布日期:2014-04-29
  • 通讯作者: 罗永龙
  • 作者简介:刘飞(1987-),男,安徽安庆人,硕士研究生,主要研究方向:信息安全;
    罗永龙(1972-),男,安徽安庆人,教授,博士,主要研究方向:信息安全;
    郭良敏(1980-),女,安徽合肥人,副教授,博士,主要研究方向:对等网络、网格;
    马苑(1988-),男,安徽合肥人,硕士研究生,主要研究方向:信息安全。
  • 基金资助:

    国家自然科学基金资助项目;安徽省自然科学基金资助项目

Trust model based on user types and privacy protection for personalized cloud services

LIU Fei1,2,3,LUO Yonglong2,3,GUO Liangmin2,3,MA Yuan2,3   

  1. 1.
    2. Engineering Technology Research Center of Network and Information Security, Anhui Normal University, Wuhu Anhui 241003, China
    3. School of Mathematics and Computer Science, Anhui Normal University, Wuhu Anhui 241003, China
  • Received:2013-10-17 Revised:2013-12-12 Online:2014-04-01 Published:2014-04-29
  • Contact: LUO Yonglong
  • Supported by:

    National Natural Science Foundation

摘要:

针对云用户难以获得个性化、高质量服务的问题,提出一种面向个性化云服务基于用户类型和隐私保护的信任模型。该模型先根据节点间的历史交易,将用户节点分为亲情节点、陌生节点及普通节点三种类型;其次,为了保护节点反馈的隐私信息,引入信任评估代理作为信任评估的主体,并且设计了基于用户类型的信任值评估方法;最后,鉴于信任的动态性,结合交易时间和交易额度提出一种新的基于服务质量的信任更新机制。实验结果表明,与AARep模型及PeerTrust模型相比,该模型不仅在恶意节点比例较低的场景中具有优势,而且在恶意节点比例超过70%的恶劣场景中,其交互成功率也分别提高了10%和16%,克服了云环境下用户节点和服务节点交互成功率低的缺点,具有较强的抵抗恶意行为的能力。

Abstract:

Concerning the problem that it is difficult for the users in cloud computing to obtain the high-quality and personalized cloud services provided by a large number of cloud providers, a trust model based on user types and privacy protection for the personalized cloud services was proposed. Firstly, the users were divided into familiar users, strange users and normal users according to the transaction history. Secondly, a fair and reasonable trust evaluation Agent was introduced to protect users' privacy, which could evaluate the trust relationship between requesters and providers based on the user types. Lastly, in view of the dynamics of trust, a new updating mechanism combined with the transaction time and transaction amount was provided based on Quality of Service (QoS). The simulation results show that the proposed model has higher transaction success rate than AARep and PeerTrust. The transaction success rate can be increased by 10% and 16% in the harsh environment where the malicious user ratio reaches 70%. This method can improve transaction success rate, and has a strong ability to withstand harsh environments.

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