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SORT: A Self-ORganizing Trust Model for Peer-to-Peer Systems

机译:SORT:对等系统的自组织信任模型

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Open nature of peer-to-peer systems exposes them to malicious activity. Building trust relationships among peers can mitigate attacks of malicious peers. This paper presents distributed algorithms that enable a peer to reason about trustworthiness of other peers based on past interactions and recommendations. Peers create their own trust network in their proximity by using local information available and do not try to learn global trust information. Two contexts of trust, service, and recommendation contexts, are defined to measure trustworthiness in providing services and giving recommendations. Interactions and recommendations are evaluated based on importance, recentness, and peer satisfaction parameters. Additionally, recommender's trustworthiness and confidence about a recommendation are considered while evaluating recommendations. Simulation experiments on a file sharing application show that the proposed model can mitigate attacks on 16 different malicious behavior models. In the experiments, good peers were able to form trust relationships in their proximity and isolate malicious peers.
机译:对等系统的开放性使它们容易受到恶意活动的攻击。在对等方之间建立信任关系可以减轻恶意对等方的攻击。本文提出了分布式算法,使对等方可以根据过去的交互和建议来推理其他对等方的可信度。对等方通过使用可用的本地信息在附近创建自己的信任网络,并且不要尝试学习全局信任信息。定义了信任,服务和推荐两种上下文,以衡量提供服务和提出建议时的可信度。根据重要性,最新性和同伴满意度参数评估互动和建议。此外,在评估建议时,还会考虑推荐人对建议的信任度和信心。在文件共享应用程序上的仿真实验表明,该模型可以减轻对16种不同恶意行为模型的攻击。在实验中,好的对等方能够在其附近形成信任关系并隔离恶意对等体。

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