Privacy Enhancing Technologies

Concepts like the Internet of Things or Big Data inherently utilize massive amounts of data containing private information collected and stored by websites, sensors, monitoring systems, auditing systems, and so on. Examples include electronic records in health care systems and location information in ubiquitous computing applications. But how can we protect the privacy of participating users while at the same time enable effective sharing and utilization of the distributed data?

There are several dimensions in the area of privacy, ranging from technical and juridical to societal and economical. While we will touch upon all these different aspects in the course, we will focus on the technical dimension. We will explore potential techniques for building new platforms, services, and tools that protect users' privacy. The study of promising component technologies ranging from advances in anonymous communication and identity management to theoretic tools like differential privacy and cryptography will be the core of this course.

The final grade of the course consists of the following components:

• Digital Exam (weighting 70%)

• Individual or group assignments (weighting 30% in total).

Final grade calculation = 0.7 * Digital Exam + 0.3 * Individual/group Assignments

A passing final grade for the course can only be earned when for all components at least a 5.0 is earned, and the weighted final grade is at least a 5.8.

In case of an insufficient final result, repair options may exist in accordance with Article 17A, Times and number of examinations, sub 1, of the Teaching and Examination Regulations, for:

• Digital Exam: Resit opportunity

• Individual/group assignments: Repair opportunity

Disclaimer: information may change depending on unforeseen circumstances or measures (see: TER Art 2, sub 5).