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Winter Semester 2022/2023

   
Title:
Type: Lecture with Exercise
Token / Number / Module number: PETS / - / 8807974094
Semester hours / Credits: 3L+1E / 6ECTS SCH / 3L+1E / 6ECTS CP
Lecturer: Prof. Dr. Frank Kargl
Tutor: Migena Ymeraj, Artur Hermann
General schedule: The lecture and exercises will be taught on campus. Lecture: Tuedays, 16:00 - 18:00, O28/1002 (starting 2022-10-18) Exercise: Wednesdays, 14:00 - 16:00, in presence O28/H21 (starting on 2022-10-19)
Learning platform: The link to the Moodle course will be provided soon.
Grade bonus: A grade bonus of 0.3 or 0.4 is given if the lab is passed successfully.
Exam dates: Oral exam by appointment

Description and general information

Integration of module into courses of studies: Informatik, M.Sc.: Praktische und Angewandte Informatik Informatik, M.Sc.: Vertiefungsfach IT-Sicherheit Informatik, M.Sc.: Vertiefungsfach Verteilte Systeme Informatik, Lehramt: Wahlfach Medieninformatik, M.Sc.: Kernfach Praktische und Angewandte Informatik Medieninformatik, M.Sc.: Vertiefungsfach IT-Sicherheit Medieninformatik, M.Sc.: Vertiefungsfach Verteilte Systeme Software-Engineering, M.Sc.: Kernfach Praktische und Angewandte Informatik Software-Engineering, M.Sc.: Vertiefungsfach IT-Sicherheit Informationssystemtechnik, M.Sc.: Wahlplicht Informatik Informationssystemtechnik, M.Sc.: Wahlpflicht
Modes of learning and teaching: Lecture Privacy Engineering and Privacy Enhancing Technologies, 3L (Prof. Dr. Frank Kargl, Dr. Christoph Bösch) Exercise Privacy Engineering and Privacy Enhancing Technologies, 1E (Migena Ymeraj, Ala'a Al-Momani)
Module authority: Prof. Dr. Frank Kargl
Lecturer: Prof. Dr. Frank Kargl
Language: English
Turn / Duration: Every winter semester / one semester
Requirements (contentual): Security of IT-Systems
Requirements (formal): None
Basis for:
Learning objectives: Participants will become familiar with modern privacy engineering. Starting from conducting Privacy Impact Assessments (PIAs) and a privacy risk analysis to designing privacy-friendly architectures all the way to application of privacy strategies and privacy enhancing technologies, the course covers the full lifecycle of privacy-friendly system design. Beyond mere theoretical knowledge, participants will practice their freshly acquired knowledge in many scenarios-based exercises.
Content: The course briefly summarizes foundations of privacy and data protection as discussed in more depth in module 71126 ("Grundlagen des Datenschutzes und der IT Sicherheit''). This includes privacy strategies, privacy design patterns and many more. The second part of the lecture then focuses on technical privacy protection discussing different privacy strategies like minimization or hiding, privacy enhancing technologies like attribute-based credentials or group/ring signatures, and also privacy aspects of user interfaces. The technical part also covers cryptographic techniques like commitment schemes, zero knowledge proofs, oblivious transfer, private information retrieval, and secure multiparty computation, which will be implemented in the exercises.
Literature: Selected literature and online resources
Grading procedure: Oral (in case of many participants written) exam at the end of the semester; no further course assessment; grade bonus if lab passed successfully
Estimation of effort: Active time: 60 h Preparation and evaluation: 120 h Sum: 180 h
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