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Existing monitoring methods have been used for network traffic and network malicious such as using a network monitoring system or network intrusion system. These systems mainly focus to capture traffic and anomaly data. After the capturing process, the data is visualized without doing any analysis on these captured network data. Besides, there are a number of tools with visualization techniques (e.g. Scatterplot, bar graph) that can be applied in the network monitoring system. The one-dimensional (1D), two-dimensional (2D), three-dimensional (3D) and high multidimensional data can be presented by using relevant visualization techniques. Most of the visualization techniques exist in generating the captured network data into informative graphical 2D or 3D view. However, there are no tools or systems that are able to identify as well as analyses the types of given network data and presents it into the robust and meaningful illustration based on user requirements. This paper explored a new algorithm that would be used to solve the constraints which have been mentioned above. We also presented how the algorithm can facilitate the current visualization methodology. By the end of this, our proposed methodology should be able to analyse different types of network data automatically and effectively.