基于文本处理技术的入侵检测研究进展

G. R. Kumar, N. Mangathayaru, G. Narasimha
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引用次数: 32

摘要

入侵检测是任何规模的组织面临的主要威胁之一。基于文本处理的入侵检测方法一直是网络与信息安全领域研究的热点之一。在这种入侵检测方法中,系统调用作为挖掘和预测入侵可能性的来源。当应用程序运行时,可能会在后台启动几个系统调用。这些系统调用构成了入侵检测的基础和决定因素。我们使用文本挖掘技术对入侵检测进行了广泛的调查,并验证了文献中发表的各种内核度量的适用性。最后提出了入侵检测的研究方向,这些方向在文献中没有详细讨论。我们希望这一调查能对使用文本挖掘技术进行入侵检测的研究人员有所帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intrusion Detection Using Text Processing Techniques: A Recent Survey
Intrusion Detection is one of the major threats for any organization of any size. The approach of intrusion detection using text processing has been one of the research interests among researchers working in the area of the network and information security. In this approach for intrusion detection, the system calls serve as the source for mining and predicting any chance of intrusion. When an application runs, there might be several system calls which are initiated in the background. These system calls form the basis and the deciding factor for intrusion detection. We perform an extensive survey on Intrusion detection using text mining techniques and validate the suitability of various kernel measures published in the literature. We finally come out with the research directions for intrusion detection which have not been discussed in detail in the literature. We hope this survey will be useful for researchers working in the direction of intrusion detection using text mining techniques.
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