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A novel self-checking pollution attackers identification scheme in wireless network coding

机译：无线网络编码中的新型自检污染攻击者识别方案

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摘要

Pollution attacks refer to ones where attackers modify and inject corrupted data packets into the wireless network with network coding to disrupt the decoding process. In the context of network coding, the epidemic effect of pollution attacks can degrade network throughput significantly because of the mixing nature of network coding. To address this issue, a number of malicious nodes identification schemes have been developed in the past. However, these schemes have their limitations and cannot effectively deal with pollution attacks. In this paper, we propose a novel light-weight Self-checking Pollution Attackers Identification Scheme (SPAIS), which can identify the pollution attackers effectively and efficiently. Through making full use of the broadcast nature of wireless media and insight that a well-behaved node can monitor its downstream neighboring nodes locally by cooperating with other nodes, SPAIS hierarchically organizes the network as levels such that the nodes in the same level can monitor their downstream level nodes cooperatively. Through the combination of theoretical analysis and extensive simulations, our experimental data demonstrates that SPAIS can more effectively identify pollution attackers with a lower cost in comparison with the existing representative schemes. For example, even if the quality of the network connection is not in good condition and the malicious nodes send only one corrupted packet, the pollution attackers can be identified with a high probability.
机译：污染攻击是指带有网络编码的攻击者修改和将损坏的数据分组重新定位的数据分组来破坏解码过程。在网络编码的背景下，由于网络编码的混合性质，污染攻击的疫情效应显着降低了网络吞吐量。为解决此问题，过去已开发了许多恶意节点识别方案。但是，这些计划具有它们的局限性，无法有效地处理污染攻击。在本文中，我们提出了一种新颖的轻量级自我检查污染攻击者识别计划（SPAIS），可以有效和有效地识别污染攻击者。通过充分利用无线媒体的广播性质和洞察力，良好的节点可以通过与其他节点协作来在本地监视其下游相邻节点，SPAIS分层组织为级别，使得同一级别中的节点可以监视其下游级别节点协同。通过理论分析和广泛的模拟的组合，我们的实验数据表明，与现有的代表计划相比，SPAIS可以更有效地识别污染攻击者，其成本较低。例如，即使网络连接的质量不处于良好状态，恶意节点仅发送一个损坏的数据包，也可以通过高概率识别污染攻击者。

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