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首页> 外文会议>2019 IEEE International Symposium on Measurements amp; Networking >Detecting cryptocurrency miners with NetFlow/IPFIX network measurements
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Detecting cryptocurrency miners with NetFlow/IPFIX network measurements

机译：使用NetFlow / IPFIX网络测量来检测加密货币矿工

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摘要

In the last few years, cryptocurrency mining has become more and more important on the Internet activity and nowadays is even having a noticeable impact on the global economy. This has motivated the emergence of a new malicious activity called cryptojacking, which consists of compromising other machines connected to the Internet and leverage their resources to mine cryptocurrencies. In this context, it is of particular interest for network administrators to detect possible cryptocurrency miners using network resources without permission. Currently, it is possible to detect them using IP address lists from known mining pools, processing information from DNS traffic, or directly performing Deep Packet Inspection (DPI) over all the traffic. However, all these methods are still ineffective to detect miners using unknown mining servers or result too expensive to be deployed in real-world networks with large traffic volume. In this paper, we present a machine learning-based method able to detect cryptocurrency miners using NetFlow/IPFIX network measurements. Our method does not require to inspect the packets' payload; as a result, it achieves cost-efficient miner detection with similar accuracy than DPI-based techniques.
机译：在过去的几年中，加密货币挖矿在互联网活动中变得越来越重要，如今甚至对全球经济产生了显着影响。这促使出现了一种新的恶意活动，称为加密劫持，它包括破坏连接到Internet的其他计算机并利用其资源来挖掘加密货币。在这种情况下，网络管理员在未经许可的情况下使用网络资源检测可能的加密货币矿工特别有意义。当前，可以使用来自已知挖掘池的IP地址列表，处理来自DNS流量的信息或直接对所有流量执行深度数据包检查（DPI）来检测它们。但是，所有这些方法仍然无法有效地检测使用未知采矿服务器的矿工，或者由于太昂贵而无法部署在流量巨大的真实网络中。在本文中，我们提出了一种基于机器学习的方法，该方法能够使用NetFlow / IPFIX网络测量来检测加密货币矿工。我们的方法不需要检查数据包的有效负载。结果，它实现了具有成本效益的矿工检测，其准确性与基于DPI的技术相似。

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