wangjh-github / AFGSM

approximate fast gradient method

Implementation of paper Scalable Attack on Graph Data by Injecting Vicious Nodes

by Jihong Wang, Minnan Luo, Fnu Suya, Jundong Li, Zijiang Yang, Qinghua Zheng

Requirements

• numpy
• scipy
• scikit-learn
• matplotlib
• tensorflow

Run the code

Here is a demo.py for you, just run python demo.py

Example output

References

Datasets

We provide two datasets in the data folder:

Cora

McCallum, Andrew Kachites, Nigam, Kamal, Rennie, Jason, and Seymore, Kristie.
Automating the construction of internet portals with machine learning.
Information Retrieval, 3(2):127–163, 2000.

and the graph was extracted by

Bojchevski, Aleksandar, and Stephan Günnemann. "Deep gaussian embedding of
attributed graphs: Unsupervised inductive learning via ranking." ICLR 2018.

Citeseer

Sen, Prithviraj, Namata, Galileo, Bilgic, Mustafa, Getoor, Lise, Galligher, Brian, and Eliassi-Rad, Tina.
Collective classification in network data.
AI magazine, 29(3):93, 2008.

Graph Convolutional Networks

Our implementation of the GCN algorithm is based on the authors' implementation, available on GitHub here.

The paper was published as

Thomas N Kipf and Max Welling. 2017.
Semi-supervised classification with graph convolutional networks. ICLR (2017).