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    夏怒, 李伟, 陆悠, 蒋健, 单冯, 罗军舟. 一种面向域间路由系统的信任模型[J]. 计算机研究与发展, 2016, 53(4): 845-860. DOI: 10.7544/issn1000-1239.2016.20151121
    引用本文: 夏怒, 李伟, 陆悠, 蒋健, 单冯, 罗军舟. 一种面向域间路由系统的信任模型[J]. 计算机研究与发展, 2016, 53(4): 845-860. DOI: 10.7544/issn1000-1239.2016.20151121
    Xia Nu, Li Wei, Lu You, Jiang Jian, Shan Feng, Luo Junzhou. A Trust Model for the Inter-Domain Routing System[J]. Journal of Computer Research and Development, 2016, 53(4): 845-860. DOI: 10.7544/issn1000-1239.2016.20151121
    Citation: Xia Nu, Li Wei, Lu You, Jiang Jian, Shan Feng, Luo Junzhou. A Trust Model for the Inter-Domain Routing System[J]. Journal of Computer Research and Development, 2016, 53(4): 845-860. DOI: 10.7544/issn1000-1239.2016.20151121

    一种面向域间路由系统的信任模型

    A Trust Model for the Inter-Domain Routing System

    • 摘要: 在域间路由系统中,边界网关协议(border gateway protocol, BGP)的运行基于对自治域路由通告行为的可信假设,给了虚假路由信息发布者可乘之机,导致影响Internet稳定运行的安全事件时有发生,然而现有研究工作并不能有效抑制虚假路由信息的产生和传播,因此提出一种面向域间路由系统的信任模型,以实现对自治域路由通告行为准确的可信评估.在该模型中,在每个评估周期,评估自治域对其邻居自治域的历史路由通告行为进行直接评估,同时收集被评估自治域的其他邻居自治域对其的直接评估,最后综合多方来源的直接评估结果计算被评估自治域的信任度.采用路由通告行为预测方法,以使直接评估结果可准确反映被评估自治域的未来路由通告行为,此外,为使评估自治域可获得充分的信任信息以保障信任度评估结果的准确性,采用信任推荐激励机制促进自治域积极参与信任推荐,自治域间相互根据对方的历史信任推荐积极性计算信任推荐概率,并基于该概率进行信任推荐.实验结果表明:相比于其他信任模型,在不同的评估环境中,信任模型的信任评估结果可更为准确地反映被评估自治域未来发布真实路由通告的可能性.

       

      Abstract: In the inter-domain routing system, the running of the border gateway protocol (BGP) is on the assumption that ASes trust each other, and there is lack of effective verification on the validity of the routing information, so the false information publishers have the chance to seriously threaten the security of the inter-domain routing system. However, the existing works can not effectively limit the generation and transmission of the false routing information, so this paper presents a trust model for inter-domain routing system to achieve the trust evaluation on the routing behavior of the ASes. In this model, the evaluator’s direct evaluation of the evaluated AS’s routing behavior and the evaluated AS’s neighbors’ direct evaluation, weight value is assigned to different direct evaluation to compute the trust degree of the evaluated AS. A routing announcement behavior prediction method is used to make the direct evaluation result accurately reflect the evaluated AS’s future probability of sending true routing information. In addition, in order to promote ASes to join in the trust recommending positively, an incentive mechanism is used, in which every AS evaluates the other ASes’ recommendation behavior in history and computes the corresponding recommendation probability for them. The simulation results show that, compared with other trust models for inter-domain routing system, the trust evaluation result of our model is more accurate to reflect the evaluated AS’s future probability of sending true routing information.

       

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