Due to the COVID-19 pandemic, the seminar is organized as an online course. The kick-off meeting, individual discussions and the final presentations are conducted remotely via online learning tools. Please subscribe to this mailing list for further information.
The seminar is concerned with privacy enhancing technologies. Different techniques for protecting the privacy of users are discussed as well as attacks against these techniques.
This seminar is a little different. It is organized like an academic conference with submissions, reviews, and presentations. The procedure is as follows:
First, you will be assigned a topic on which you will write a seminar paper. This paper can be written in English or German and should discuss the given topic. Keep in mind that this paper is your own contribution. Do not copy or plagiarize text from others. Write the paper in a way that your fellow students can easily follow and learn something from it.
Second, there will be a submission deadline. By this deadline, submit your paper and upload it to our conference submission system. In this system, your submission will be assigned to other students for review. Likewise, you will receive the other students' papers for review. Read the papers carefully and make constructive suggestions to improve them. The goal of this process is to make all papers in the seminar better.
Third, you will receive the reviews for your paper. You can now incorporate the feedback to improve your work. Prepare a revised version of your paper and submit it by the final submission deadline of the seminar (called camera-ready deadline).
Finally, it is time for the conference. The seminar will be held as a block course, and all students will present talks on their papers. These presentations are about 20-25 minutes long and should convey the main message of your paper. Prepare the talks alsonfor your fellow students so that they learn about your topic. If possible, we will provide food and drink during the breaks, just like at a real conference.
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The Tor network is currently the most popular low-latency anonymization network and protects the privacy of more than a million users every day. Your work is supposed to give an overview on the Tor network and discuss the techniques that are used by the network to provide anonymity to its users.
A large number of online shops and ad networks use techniques that allow a precise (re-)identification of individual internet users across multiple websites. To this end, various information leaked by the web browser is accumulated and linked to a user, thus allowing companies to track a users browsing behaviour with high precision. Your work will discuss commonly used techniques and defenses for browser fingerprinting.
Similar to browser fingerprinting, there are corresponding techniques to track mobile devices and to re-identify a specific user.
Since its introduction in 2008, the popularity of the digital currency Bitcoin is steadily growing and Bitcoin has thus become an accepted payment option in many stores worldwide. Your work will explain the principle ideas on which Bitcoin is based upon. Moreover, it should discuss its strengths and weaknesses compared to other digital currencies.
An image can be linked to a specific camera due to the camera sensor fingerprint. While this forensic technique may help in identifying fraud, a reporter however needs a way to publish sensitive images without tracing these images back to her/him. This paper examines the different image anonymization methods against camera fingerprints.
Given query access to a learning-based system, adversaries can find out if a data record (e.g., a person) was part of the training data. This can lead to serious privacy violations, for instance, if an attacker can find out if a person participated in a medical study. Your work gives an overview of different membership-inference attacks and defenses.
Given query access to a learning-based system, adversaries can also try to recover the learning model. Your work examines different types of attacks and defenses, with a major focus on structured data, such as text, source code or malware.
Futher topics are possible, e.g., adversarial examples for privacy, differential privacy, PIN cracking, and many more..