  This paper has dual aims. First is to develop practical universal coding
methods for unlabeled graphs. Second is to use these for graph anomaly
detection. The paper develops two coding methods for unlabeled graphs: one
based on the degree distribution, the second based on the triangle
distribution. It is shown that these are efficient for different types of
random graphs, and on real-world graphs. These coding methods is then used for
detecting anomalous graphs, based on structure alone. It is shown that
anomalous graphs can be detected with high probability.
