1. Method for detecting an anomaly in a network comprising a feature value generating step for counting the number of packets per each time slot for each traffic type with respect to the traffic of a network, and generating it as a feature value; a correlation coefficient calculating step for taking the feature value of each traffic type generated via the feature value generating step, and calculating correlation coefficients between each pair of two feature values; a histogram generating step for generating a histogram from the correlation coefficients for each pair of two feature values; and an anomaly severity determining step for determining the severity of an anomaly of interest using the histograms generated via the histogram generating step, the method further comprising a state similarity evaluating step for evaluating the similarity of the anomaly of interest to a reference anomaly using the occurrence probabilities of correlation coefficients used for the construction of a histogram; and a visualizing step for expressing the occurrence probabilities of correlation coefficients calculated via the state similarity evaluating step as a matrix and assigning colors to the occurrence probabilities of the matrix for the visualization of the matrix.