rAnPriv (Lite) ~ Privacy-Preserving Online Social Network Information Disclosure Scheme

Introduction

This is the experimental code for privacy-preserving online social network information disclosure scheme, which is my undergoing Master's project.

The datasets used in this project are from Stanford Large Network Dataset Collection.

Currently, we support the following two datasets.

Note: The code is written in Python 2.7.x. Currently, it is not compatible with Python 3 (But in progress).

	$ git clone https://github.com/rAnYKM/rAnPriv.git
	$ cd rAnPriv
	$ pip install -r requirements.txt

For Windows, I strongly recommend to use the Anaconda for the best experience.

Configure the directory of the SNAP datasets.

	$ python ranfig.py -g $GOOGLE_PLUS_DIR$ -f $FACEBOOK_DIR$ -d data -o out

	>>> from snap_facebook import FacebookEgoNet
	>>> facebook = FacebookEgoNet('0')
	>>> facebook.ran.soc_net.number_of_nodes()
	348

    >>> from ran_priv import RPGraph

Name		Name	Last commit message	Last commit date
Latest commit History 107 Commits
data		data
deprecated		deprecated
out		out
.gitattributes		.gitattributes
.gitignore		.gitignore
README.md		README.md
data_display.py		data_display.py
experiment_note.txt		experiment_note.txt
ran_graph.py		ran_graph.py
ran_inference.py		ran_inference.py
ran_kp.py		ran_kp.py
ran_lab.py		ran_lab.py
ran_priv.py		ran_priv.py
ranfig.py		ranfig.py
requirements.txt		requirements.txt
snap_facebook.py		snap_facebook.py
snap_fbcomplete.py		snap_fbcomplete.py
snap_google.py		snap_google.py
snap_gpcomplete.py		snap_gpcomplete.py
test.py		test.py
viztool.py		viztool.py