Abstract
In this chapter, a new review and taxonomy of the input data and pre-processing techniques of intrusion detection systems are presented. This chapter surveys the literature over the last two decades on the data of intrusion detection systems. We present also in this chapter a framework for understanding the different components described in the literature that allows readers to systematically understand the works and envision future hybrid approaches. The chapter describes how to collect the data, and how to prepare this data for different types of processing. We opted to organize the chapter along a component-by-component structure, rather than a paper-by-paper organization, since we believe this will give the reader a wider perspective about the process of constructing an intrusion detection system and its evaluation mechanisms. The organization of this chapter represents an ideal intrusion detection system since it contains most of the components of IDS, so existing approaches can be neatly accommodated within this framework. This will allow the reader to construct and explore new systems by assembling the described components in novel arrangements. We have also conducted important comparisons after each component of IDS supported by some tables to give the reader a better perspective about that particular component. In this sense, it provides insights that a reader would not gain by simply reading the original source papers. The classifiers used with IDS are beyond the scope of this chapter.
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Hamed, T., Ernst, J.B., Kremer, S.C. (2018). A Survey and Taxonomy on Data and Pre-processing Techniques of Intrusion Detection Systems. In: Daimi, K. (eds) Computer and Network Security Essentials. Springer, Cham. https://doi.org/10.1007/978-3-319-58424-9_7
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