Detecting anomalous network hosts by means of PCA

T. Pevný, M. Rehák, Martin Grill
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引用次数: 11

Abstract

This paper focuses on the identification of anomalous hosts within a computer network with the motivation to detect attacks and/or other unwanted and suspicious traffic. The proposed detection method does not use content of packets, which enables the method to be used on encrypted networks. Moreover, the method has very low computational complexity allowing fast detection and response important for limitation of potential damages. The proposed method uses entropies of IP addresses and ports to build two complementary models of host's traffic based on principal component analysis. These two models are coupled with two orthogonal anomaly definitions, which gives four different detectors. The methods are evaluated and compared to prior art on one week long capture of traffic on university network. The experiments reveals that no single detector can detect all types of anomalies, which is expected and stresses the importance of ensemble approach towards intrusion detection.
基于PCA的异常网络主机检测
本文主要研究计算机网络中异常主机的识别,目的是检测攻击和/或其他不需要的和可疑的流量。提出的检测方法不使用数据包的内容,这使得该方法能够在加密网络上使用。此外,该方法具有非常低的计算复杂度,允许快速检测和响应,这对限制潜在损害至关重要。该方法利用IP地址和端口的熵,基于主成分分析建立主机流量的两个互补模型。这两种模型与两种正交的异常定义相结合,得到了四种不同的检测器。对这些方法进行了评估,并与现有技术进行了为期一周的大学网络流量捕获进行了比较。实验表明,没有一个单一的检测器可以检测到所有类型的异常,这是预期的,并强调了集成方法在入侵检测中的重要性。
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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