Pre-Processing of KDD’99 & UNSW-NB Network Intrusion Datasets
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Abstract
An IDS is essential for securing the network. The IDS not only traverses the header portion of the network packet but also inspects the data portion or the payload of the network packet. Therefore, if at all any malicious code is present in the data portion, it would be detected by the IDS and the packet will be denied access to the network or removed accordingly. Various datasets on computer and network intrusions are available publicly and are extensively used in developing successful intrusion detection systems. In this development process pre-processing plays an important role to make the data ready for the prediction process. This paper presents and analyses on two widely used datasets - KDD’99 and UNSW-NB 15 in intrusion detection. Pre-processing of both the datasets is performed considering missing, redundant and noisy data along with the data cleaning process using Weka data miner tool. A brief discussion on a newly created dataset is also presented in the paper.
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