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Nowadays, many computers have been infected with the computer anomalies or viruses. The availability of network security visualization tools greatly facilitate to detect, perceive and defend computer users from being affected by these anomalies. Many of the network security visualization tools are designed particularly for users with advanced network security awareness even though the tools are indispensable by various types of computer users. We proposed an expert-aware approach to designing a system which formulated with a large amount of network data or high-dimensional data and adaptive for different types of users. In the preliminary phase, we proposed and implemented initial pre-expertise classification system which provides a default setting for the expert-aware network security visualization tool. The tool will learn from continual user feedbacks in order to statistically satisfy the needs of majority tool users. The expert-aware approach looks at the users' expertise level in network security and adapts the visualization views that are best suitable for the user. Initial results of the implementation of the system show that it is capable of representing several of network security data not only on two-dimensional space on a computer but also beyond that space. Systems features, such as system effectiveness and efficiency of data visualization have been improved. Our experiments in a network lab suggest that the tool can be further improved as the tool for distribution to a wide range of computer user.