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Study on Trust Inference and Emergence of Economical Small-World Phenomena in P2P Environment

机译:P2P环境下经济小世界现象的信任推理与产生研究

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摘要

With the increasing popularity of self-organized communication systems, distributed trust and reputation systems in particular have received increasing attention. By formalizing trust relationships, trust between parties within the community can be derived by analyzing the trust paths linking the parties together. This paper treats trust network as an emergent property. The emergence interpretation concerns both the maintenance and usage of trust network inference. Specifically, in P2P system, trust network is maintained by individual agents at micro level, and it is used (i.e., queried) as one entity at macro level. In this paper, we first discuss micro level activities, that is, we classifies trust into functional trust and referral trust to facilitate trust inference, and extend the referral trust to include factors of similarity and truthfulness, so that our approach can accommodate the personalized feature of reputation rating, and reduce trust inference error effectively; then we discuss macro level properties of trust network. Specifically, we investigate the emergence of network structural properties of trust and reputation system in terms of efficiency and cost. That is, efficiency measures how well information propagates over trust system, and cost measures how expensive it is to build this system. Preliminary simulation results show the performance improvement of P2P community and the emergence of economical small-world trust network, namely relatively high efficiency and low cost.
机译:随着自组织通信系统的日益普及,尤其是分布式信任和信誉系统受到了越来越多的关注。通过形式化信任关系,可以通过分析将各方联系在一起的信任路径来得出社区内各方之间的信任。本文将信任网络视为一种新兴属性。出现解释涉及信任网络推理的维护和使用。具体地,在P2P系统中,信任网络由各个代理在微观级别维护,并且它被用作(即,被查询)为宏级别的一个实体。在本文中,我们首先讨论微观活动,即将信任分为功能性信任和引用信任,以促进信任推理,并将引用信任扩展到包含相似性和真实性的因素,以便我们的方法可以适应个性化特征。信誉评价,有效减少信任推理错误;然后讨论了信任网络的宏观属性。具体来说,我们从效率和成本的角度研究信任和信誉系统的网络结构属性的出现。也就是说,效率衡量信息在信任系统上的传播情况,而成本衡量构建此系统的成本。初步的仿真结果表明,P2P社区的性能得到改善,经济型小世界信任网络的出现,即效率相对较高,成本较低。

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