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Behavior-based reputation management in P2P file-sharing networks

机译:P2P文件共享网络中基于行为的信誉管理

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摘要

Trust research has become a key issue in the last few years as a novel and valid solution to ensure the security and application in peer-to-peer (P2P) file-sharing networks. The accurate measure of trust and reputation is a hard problem, most of the existing trust mechanisms adopt the historical behavior feedback to compute trust and reputation. Thus exploring the appropriate transaction behavior becomes a fundamental challenge. In P2P system, each peer plays two roles: server and client with responsibility for providing resource service and trust recommending respectively. Considering the resource service behavior and trust recommending behavior of each peer, in this paper, we propose a new trust model adopting the technology to calculate eigenvectors of trust rating and recommending matrices. In our model, we define recommended reputation value to evaluate the resource service behavior, and recommending reputation value to evaluate the trust recommendation behavior. Our algorithm would make these two reputation values established an interrelated relation of reinforcing mutually. The normal peers provide authentic file uploading services, as well as give correct trust recommendation, so they can form a trusted and cooperative transaction community via the mutual reinforcement of recommended and recommending reputation values. In this way, the transaction behaviors of those malicious peers are isolated and confined effectively. Extensive experimental results also confirm the efficiency of our trust model against the threats of exaggeration, collusion, disguise, sybil and single-behavior.
机译:过去几年来,信任研究已成为一个关键问题,它是一种新颖且有效的解决方案,可确保对等(P2P)文件共享网络的安全性和应用程序。信任和声誉的准确度量是一个难题,大多数现有的信任机制都采用历史行为反馈来计算信任和声誉。因此,探索适当的交易行为成为一项基本挑战。在P2P系统中,每个对等方分别扮演两个角色:服务器和客户端,分别负责提供资源服务和信任推荐。考虑到每个对等体的资源服务行为和信任推荐行为,本文提出了一种新的信任模型,该模型采用了该技术来计算信任等级的特征向量并推荐矩阵。在我们的模型中,我们定义推荐信誉值以评估资源服务行为,并定义信誉值以评估信任推荐行为。我们的算法将使这两个信誉值建立相互增强的相互联系的关系。普通对等方提供可靠的文件上传服务,并给出正确的信任推荐,因此它们可以通过相互加强推荐和推荐信誉值来形成一个受信任的合作交易社区。这样,可以有效隔离和限制那些恶意对等方的交易行为。广泛的实验结果还证实了我们的信任模型在抵御夸大,串通,伪装,sybil和单行为的威胁方面的有效性。

著录项

  • 来源
    《Journal of computer and system sciences》 |2012年第6期|p.1737-1750|共14页
  • 作者单位

    School of Software, Dalian University of Technology, Dalian 116620, Liaoning, PR China;

    School of Software, Dalian University of Technology, Dalian 116620, Liaoning, PR China;

    Faculty of Computer & Information Sciences, Hosei University, 3-7-2, Kajino-cho, Koganei-shi Tokyo 184-8584, Japan;

    School of Software Engineering, Hangzhou Diana University, Hangzhou 310018, Zhejiang, PR China;

    School of Computer Science & Technology, Shandong University of Technology, Zibo 255000, Shandong, PR China;

    School of Software, Dalian University of Technology, Dalian 116620, Liaoning, PR China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    peer-to-peer file-sharing network; reputation; collusion; trust community;

    机译:对等文件共享网络;声誉;共谋;信任社区;

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