PDNS-Net: A Large Heterogeneous Graph Benchmark Dataset of Network Resolutions for Graph Learning

Understand

In order to advance the state of the art in graph learning algorithms, it is necessary to construct large real-world datasets.

• While there are many benchmark datasets for homogeneous graphs, only a few of them are available for heterogeneous graphs.
• Furthermore, the latter graphs are small in size rendering them insufficient to understand how graph learning algorithms perform in terms of classification metrics and computational resource utilization.
• We introduce, PDNS-Net, the largest public heterogeneous graph dataset containing 447K nodes and 897K edges for the malicious domain classification task.