In this study project the participants will acquire practical skills in the application of machine learning (ML) techniques in the area of IT security in adversarial settings. The field of ML is playing an ever increasing role in computer science in general and IT security in particular. The idea of the project is to mount traffic analysis attack on the encrypted and anonymized connections. To this end, students will develop scripts to automate fetching of different websites from a web browser while applying various privacy enhancing techniques (e.g., VPN, SSH tunnel, Tor network). By doing so, they will collect traces of encrypted data that will be further used for feature engineering and extraction, training and testing of different machine learning techniques. Finally, students will analyze the results in the form of different quality metrics and will write a report and present the results.
In the form of a self organized study project the participants get familiar and/or deepen their knowledge in machine learning, especially support vector machines and their applications to traffic analysis. The participants get deep insights in the state of the art research in traffic analysis and apply the existing knowledge to build, test, and evaluate their own website fingerprinting attack.
Please enroll here for the moodle course.
|Wednesday||15:30 - 17:00||VG 1C/0.03|
|Wednesday||17:30 - 19:00||VG 1C/0.03|