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Malicious peers eviction for P2P overlays

机译:P2P覆盖的恶意同伴驱逐

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P2P networks constitute the foundation for many scalable and fault-tolerant applications. These networks may consist of millions of peers due to their decentralized design. While each peer advertises the same service interface, the actual data provided by common large-scale P2P applications often yields an imbalance, i.e., particular peer subsets are more frequently contacted than the rest of the overlay. Such subsets may refer to peers that replicate critical or popular content. As a consequence, Localized Attacks (LA) target these subsets and despite using a relatively small amount of attacking malicious peers, LAs severely impair the overall network's reliability. Hence, we propose a new two-fold LA countermeasure to detect and evict malicious peers. Our countermeasure has been evaluated in a comprehensive simulation experiment study using a generic LA model that covers a wide range of known LAs such as Sybil, Eclipse or different poisoning attacks. The study shows reliability improvements of up to 97% in the presence of LAs, as well as successful evictions for up to 99% of the cases.
机译:P2P网络构成了许多可伸缩和容错应用程序的基础。由于其分散的设计,这些网络可能包含数百万个对等点。虽然每个对等方通告相同的服务接口,但由常见的大型P2P应用程序提供的实际数据通常会产生不平衡,即与覆盖中的其余部分相比,联系特定对等方子集的频率更高。这样的子集可以指复制关键或流行内容的同级物。结果,局部攻击(LA)瞄准了这些子集,尽管使用了相对少量的攻击恶意对等体,但LA严重损害了整个网络的可靠性。因此,我们提出了一种新的双重LA对策来检测和驱逐恶意对等体。我们的对策已通过使用通用LA模型的综合模拟实验研究进行了评估,该模型涵盖了广泛的已知LA,例如Sybil,Eclipse或其他中毒攻击。该研究表明,在存在洛杉矶的情况下,可靠性提高了多达97%,并且成功驱逐了多达99%的案件。

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