Multi-dimensional data visualization using concentric coordinates

This paper proposes a new method called Concentric Coordinate for visualizing multidimensional datasets. To reduce the overlapping and edge crossings among curves, axes are arranged as concentric circles rather than parallel lines that are commonly used in the traditional approach. Edges which represent data items are drawn as segments of curves rather than poly-lines drawn in the classical parallel coordinate approach. Some heuristics are applied in our new method in order to improve the readability of views. The paper demonstrates the advantages of new method. In comparison with the parallel coordinate method, our concentric circle approach can reduce more than 15 % of the edge overlaps and crossings by visualizing the same dataset. In our new approach, we further enhance the readability of views by increasing the crossing angle. Finally, a visual interactive network scans detection system called CCScanViewer is developed based on our new visualization method to represent traffic activities in network flows, and the experiments show that the new approach is effective in detecting unusual patterns of network scans, port scans, the hidden scans, DDoS attacks etc