Author: Yinzhi Cao, Song Li, Erik Wijmans

Group: System Security Lab in Johns Hopkins University

Website: http://uniquemachine.org

Paper: Paper

The master branch is used for testing purposes only. If you want to deploy it and collect browser fingerprints, please visit the aws_deploy branch.

Demo

Related repo: https://github.com/Song-Li/LanguageDetector Used to detect supported languages

This is a project for a browser fingerprinting technique that can track users not only within a single browser but also across different browsers on the same machine.

Specifically, our approach utilizes many novel OS and hardware level features, such as those from graphics cards, CPU, and installed writing scripts (Implementing). We extract these features by asking browsers to perform tasks that rely on corresponding OS and hardware functionalities.

In this project, we have a client side, web-based application, and a backend flask server file. The server side is written in Python 2.

• Change the YOURSERVER text at Line 286 of the ./client/fingerprint/js/details.js file to your server address.
• Change the YOURSERVER text at Line 2 of the ./client/fingerprint/js/toServer.js file to your server address.
• Host the client side files by running python -m http.server 9876 (for python 3) or python -m SimpleHTTPServer 9876 (for python 2)

• Install the dependencies by running pip install -r requirements.txt in the root dir of the project folder
• Start the server by running python flask/server.py

After you deployed the client side and the server side, you can start to play with it by visiting localhost:9876

The whole client part is JS based in "client" dir. Some of the modules are generated from C or coffee. Here is a list of usful description of dirs in "client":

• fingerprint: Including all files related to fingerprinting tests.
• js: Javascript part used for index.html

The server part is writen in python. Using apache2 and flask as the framework.