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This paper presents a visual analysis of the UNSW-NB25 computer networksecurity or intrusion detection dataset in order to detect any issues inherentto this dataset which may require researchers to address before employing thisdataset for data-driven model development such as a machine learningclassifier. A number of data preprocessing algorithms are applied on the rawdata to address common issues such as elimination of redundant features,conversion of nominal features into numerical format and scaling. PCA, t-SNEand K-means clustering algorithms are employed for developing the graphs andplots for visualization. Consequent analysis through visualization identifiedand illustrated two major problems as class imbalance and class overlap forthis dataset. In conclusion, it is necessary to address these two problems ofclass imbalance and class overlap prior to employing this dataset for anyclassifier model development.

UNSW-NB15 Computer Security Dataset: Analysis through Visualization