Know your Victim: Tor Browser Setting Identification via Network Traffic Analysis

Objective

• A crawler implementation that can collect the website traffic with different browser settings
• A naive browser classifier implementation to predict the Tor browser version and security setting given network traffic
• Code for feature extraction given the raw network pcap file
• Verification regarding Tor browser settings' impacts on network traffic patterns

Dataset

• Google drive: https://drive.google.com/drive/folders/1dB7FJGCpHzYL1CnevsV-sLqHcx-zs-l8?usp=sharing

version and security setting datasets are included in the link

Crawler Setup

Docker

$ change code/Config.py(torbrowser directory to either torbrowser_902 | torbrowser_806 | torbrowser_752)
$ change Dockerfile, change argument in code/setup.sh to the specific torbrowser version
$ docker build -t <imageName> .
$ ./run.sh <image_name> <container_name> <outputdir>(volume)

Feature Exctraction

$ cd code
$ pip3 install -r requirements.txt
$ python3 FeatureExtract.py -i <TrafficDir> -o <outputdir>

<TrafficDir>: in csv form(the output of pcapParser)

Random forest based Browser Setting classifier

$ cd code/
$ pip3 install -r requirements.txt
$ cd code/browserclassifier/
$ pip3 install -r mlrequirements.txt
$ configure the MLConfig.py
$ python3 browserClassifier.py -i <Traffic feature dir, the outputdir of feature extraction> -o <outputdir>