Author: Yinzhi Cao, Song Li, Erik Wijmans
Group: SECLAB in Johns Hopkins University
Website: http://uniquemachine.org
Paper: https://drive.google.com/file/d/0B4s900Byvv1ibW5uc1NiU2g3R3c/view
The repo will be rebuilt from 2018 Oct. 10th to Dec. 1st
Demo This is only a DEMO. Only 2 features in the paper is implemented. Far from finished. 10 ~20 features is waiting for implementation, more masks for GPU and Fonts needed to be updated. The research code can't be used directly...
Related repo: https://github.com/Song-Li/LanguageDetector Used to detect supported languages
Development: Currentlly I'm focusing on another related project. I will update this repo when I'm free
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.
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.