Skip to content

Sybil account detection on the dark web drug markets using an unsupervised multi-view learning approach. Worked while I was at Knoesis.

License

Notifications You must be signed in to change notification settings

RamnathKumar181/eDarkFind-Unsupervised-Multi-view-Learning-for-Sybil-Account-Detection

Repository files navigation

eDarkFind

This repository contans the the source code for the paper - eDarkFind: Unsupervised Multi-view Learning for Sybil Account Detection. For more information about the code, refer to Paper or the Slides.

Requirements

  • Python 3.6
  • keras : pip install keras
  • numpy : pip install numpy
  • sklearn : pip install sklearn

System Used

  1. CPU: Intel(R) Xeon(R) CPU @ 2.30GHz
  2. GPU: 1xTesla K80 , having 2496 CUDA cores, compute 3.7, 12GB(11.439GB Usable) GDDR5 VRAM
  3. RAM: 12.6GB

Acknowledgements

I would like to thank Dr. Amit Sheth, Dr. Prasad and all the collaborators for giving me the opportunity to work on this project

About

Sybil account detection on the dark web drug markets using an unsupervised multi-view learning approach. Worked while I was at Knoesis.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Languages