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An Analytical Model for the Partial Intercept Probability in Sparse Linear Network Coding
IEEE Communications Letters ( IF 4.1 ) Pub Date : 2020-04-01 , DOI: 10.1109/lcomm.2020.2969349
Hadi Sehat , Peyman Pahlevani

The security of linear network coding schemes such as Random Linear Network Coding (RLNC) and Sparse Random Linear Network Coding (SRLNC) is an important performance metric. One of the security aspects of these coding schemes is the probability that a potential eavesdropper recovers a fraction of source packets. In this work, we consider a network consisted of a sender, a legitimate receiver and an eavesdropper, where the sender uses SRLNC to broadcast data. We propose an analytical approximation for the probability of decoding a fraction of source packets, i.e., the partial intercept probability, by the eavesdropper. Using this analytical model, we propose an algorithm for the maximum sparsity that satisfies a threshold on the number of the source packets decoded by the eavesdropper. Using simulation technique, We proved that the maximum sparsity found by this algorithm satisfies the aforementioned threshold.

中文翻译:

稀疏线性网络编码中部分截获概率的解析模型

诸如随机线性网络编码 (RLNC) 和稀疏随机线性网络编码 (SRLNC) 等线性网络编码方案的安全性是一个重要的性能指标。这些编码方案的安全方面之一是潜在窃听者恢复部分源数据包的可能性。在这项工作中,我们考虑一个由发送者、合法接收者和窃听者组成的网络,其中发送者使用 SRLNC 来广播数据。我们为窃听者解码一小部分源数据包的概率(即部分拦截概率)提出了一种解析近似。使用这个分析模型,我们提出了一种最大稀疏度的算法,该算法满足窃听者解码的源数据包数量的阈值。使用模拟技术,
更新日期:2020-04-01
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