KarmaNET:利用可信的社会路径创建明智的转发器

M. Spear, Xiaoming Lu, N. Matloff, S. F. Wu
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引用次数: 14

摘要

分布式系统中存在的许多问题都与路由与信任正交而忽略了社会连通性有关。本文提出了一种新颖的、经济的协议——KarmaNET,它将任何路由协议与信任绑定在一起,以建立一个可信的社会路径,并创建明智的转发器。这为节点创造了建立善业的激励,并消除了积累了太多恶业的节点。KarmaNET只需要本地知识,从源头切断恶意节点,适应行为的动态变化,限制节点在其生命周期内可以生成的不想要的消息的数量(即使在存在共谋、兼职垃圾邮件发送者和标记结果错误的情况下),并在限制内实现每个节点接收到的预期0垃圾邮件。KarmaNET排斥垃圾邮件发送者、吃白吃的人,并以可忽略不计的假阳性和阴性率(小于0.5%)最大限度地减少Sybil攻击。我们从理论上证明了攻击者可能造成的损害的界限,KarmaNET对节点的动态行为实现了指数级的快速适应,并表明我们的仿真与理论相匹配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
KarmaNET: Leveraging trusted social paths to create judicious forwarders
Many existing problems in distributed systems can be linked to routing being orthogonal to trust and ignoring the social connectivity. This paper introduces a novel and economical protocol, entitled KarmaNET, which binds any routing protocol with trust to build a trusted social path and create judicious forwarders. This creates incentives for nodes to build good karma, and excises any node that has accumulated too much bad karma. KarmaNET requires only local knowledge, cuts off malicious nodes at the source, adapts to dynamic changes in behavior, bounds the number of unwanted messages a node can generate in its lifetime (even in the presence of collusion, part-time spammers, and errors in marking the outcome), and achieves an expected 0 spams received per node in the limit. KarmaNET ostracizes spammers, freeloaders, and minimizes Sybil attacks with negligible false positive and negative rates (less than 0.5%). We theoretically prove bounds on the damage an attacker can cause, that KarmaNET achieves exponentially fast adaptation to a node's dynamic behavior, and show that our simulation matches the theory.
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