Collaborative approach for inter-domain botnet detection in large-scale networks

Hachem Guerid, Karel Mittig, A. Serhrouchni
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引用次数: 5

Abstract

The members of almost all botnets are distributed between several networks. Such distribution hardens their detection as the centralized approaches require to centralize network data for their analysis, which is indeed not possible in regard to the legacy and business constraints applied to network operators. In this paper, we propose a collaborative and inter-domain botnet detection system which conciliates the requirements of privacy and business preservation, while enabling realtime analysis for large scale networks. The different probes of our collaborative detection system exchange anonymised information in order to synchronize the network analysis of the members of botnets and to identify the malicious servers controlling them. We evaluated our system using anonymised traffic captured on an operator's network, and the results showed an improvement of 31% of malicious servers detected resulting from the collaboration, and this without significant performance impact and bandwidth overhead (respectively 4% and 11kb/s).
大规模网络域间僵尸网络检测的协同方法
几乎所有僵尸网络的成员都分布在几个网络之间。这种分布强化了它们的检测,因为集中式方法需要将网络数据集中起来进行分析,而考虑到应用于网络运营商的遗留问题和业务约束,这确实是不可能的。在本文中,我们提出了一个协作和跨域的僵尸网络检测系统,它协调了隐私和业务保护的要求,同时能够对大规模网络进行实时分析。我们协作检测系统的不同探针交换匿名信息,以同步僵尸网络成员的网络分析并识别控制它们的恶意服务器。我们使用在运营商网络上捕获的匿名流量对我们的系统进行了评估,结果显示,由于协作,检测到的恶意服务器的数量提高了31%,这没有显著的性能影响和带宽开销(分别为4%和11kb/s)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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