A self-adaptive probabilistic packet filtering scheme against entropy attacks in network coding
A self-adaptive probabilistic packet filtering scheme against entropy attacks in network coding
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DOI：
10.1016/j.comnet.2009.08.002
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发表时间：
2009-12
期刊：
影响因子：
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通讯作者：
Yixin Jiang;Yanfei Fan;Xuemin Shen;Chuang Lin
中科院分区：
文献类型：
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作者：
Yixin Jiang;Yanfei Fan;Xuemin Shen;Chuang Lin
本文基于一种新的自适应概率子集线性相关检测（S-PSLD）算法，提出了一种有效的网络编码中抗熵攻击的包过滤方案。该方案对接收到的数据包进行概率验证，而不是精确验证，因此可以快速过滤出熵攻击的结果。此外，为了最大限度地减少数据包检测的成本，同时保持在一个预期的低水平的误报率，自适应算法的引入，使每个转发器可以动态地调整系统的安全参数，根据可用带宽或在缓冲区中接收到的数据包的数量。理论分析和性能评估证明了该方案的有效性和高效性。
In this paper, based on a novel self-adaptive probabilistic subset linear-dependency detection (S-PSLD) algorithm, we propose an efficient packet filtering scheme against entropy attacks in network coding. The scheme verifies the received packets probabilistically instead of exactly, and thus it can rapidly filter out the resultant packets from entropy attacks. Moreover, to minimize the packet detection cost at forwarder while keeping the false positive rate at an expected low level, a self-adaptive algorithm is introduced such that each forwarder can dynamically tune the system security parameters according to the available bandwidth or the number of the received packets in buffer. Theoretical analysis and performance evaluation are given to demonstrate the validity and efficiency of the proposed scheme.