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Intrusion detection is one of the important measures to guarantee the security of network. The growing diversity and concealment of network attacks lead to the difficult of intrusion detection, which make the research for new intrusion detection method is urgent. Combined with visualization technology and k-Nearest Neighbor classifier, an intrusion detection method based on graphical feature is proposed in this paper. The information gain method is used to rank the original features, and the front features are selected for radar chart visualization presentation. After a new dataset based on the graphical features is generated, k-Nearest Neighbor classifier is applied to train and test it. The results of experiment based on KDDCUP99 dataset show that the proposed method can not only visualize the attacks, but also has really satisfactory performance of intrusion detection, with 97.9% detection rate and 1.4% false positive rate for DOS.