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Secure Network Code for Adaptive and Active Attacks with No-Randomness in Intermediate Nodes
arXiv - CS - Information Theory Pub Date : 2017-12-25 , DOI: arxiv-1712.09035
Ning Cai and Masahito Hayashi

In secure network coding, there is a possibility that the eavesdropper can improve her performance when she changes (contaminates) the information on the attacked edges (active attack) and chooses the attacked edges adaptively (adaptive attack). We analyze the security for network code over such types of attacks. We show that active and adaptive attacks cannot improve the performance of the eavesdropper when the code is linear. Further, we give a non-linear example, in which an adaptive attack improves the performance of the eavesdropper. We derive the capacity for the unicast case and the capacity region for the multicast case or the multiple multicast case in several examples of relay networks, beyond the minimum cut theorem, when no additional random number is allowed as scramble variables in the intermediate nodes. No prior study compared the difference of the capacity and the capacity region between the existence and the non-existence of randomness in the intermediate nodes under these network models even with non-adaptive and non-active attacks.

中文翻译:

用于中间节点无随机自适应和主动攻击的安全网络代码

在安全网络编码中,当窃听者改变(污染)被攻击边(主动攻击)的信息并自适应地选择被攻击边(自适应攻击)时,窃听者有可能提高她的性能。我们分析了网络代码对此类攻击的安全性。我们表明,当代码是线性的时,主动和自适应攻击不能提高窃听者的性能。此外,我们给出了一个非线性示例,其中自适应攻击提高了窃听者的性能。我们在中继网络的几个例子中推导出单播情况的容量和多播情况或多播情况的容量区域,超出最小割定理,当中间节点中不允许额外的随机数作为加扰变量时。
更新日期:2020-03-27
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