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Author: Meng Jiang ([email protected]). PAKDD'14/KAIS'16. Suspicious behavior detection. Graph anomaly detection. Graph mining.

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LockInfer

This repository contains the code package for the PAKDD'14 / KAIS'16 paper:

Inferring Strange Behavior from Connectivity Pattern in Social Networks.

Inferring Lockstep Behavior from Connectivity Pattern in Large Graphs.

Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang.

Usage

A toy example to generate the injected graph and use Get-the-Scoop to detect the injected node groups.

  1. Python: Run graph_generator.py
  2. Matlab: Run run_compute_eigenvector.m
  3. R: Run plot_eigenvector.R
  4. Python: Run get_the_scoop.py

Citation

If you find this repository useful in your research, please cite our paper:

@incollection{jiang2014inferring,
  title={Inferring Strange Behavior from Connectivity Pattern in Social Networks},
  author={Jiang, Meng and Cui, Peng and Beutel, Alex and Faloutsos, Christos and Yang, Shiqiang},
  booktitle={Advances in Knowledge Discovery and Data Mining},
  pages={126--138},
  year={2014},
  publisher={Springer}
}

@article{jiang2016inferring,
  title={Inferring lockstep behavior from connectivity pattern in large graphs},
  author={Jiang, Meng and Cui, Peng and Beutel, Alex and Faloutsos, Christos and Yang, Shiqiang},
  journal={Knowledge and Information Systems},
  volume={48},
  number={2},
  pages={399--428},
  year={2016},
  publisher={Springer}
}

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Author: Meng Jiang ([email protected]). PAKDD'14/KAIS'16. Suspicious behavior detection. Graph anomaly detection. Graph mining.

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  • Python 77.7%
  • R 12.0%
  • MATLAB 9.1%
  • Makefile 1.2%