MDPPML University of Tübingen

Teaching

We teach cryptography and privacy-enhancing technologies at the University of Tübingen, from an introductory lecture to a hands-on practical course and a research seminar.

Course
INFO4451
When
Summer semester
Format
Lecture
Lecturer
Mete Akgün
Tutors
Şeyma Selcan Mağara, Cem Ata Baykara

Introduction to Cryptography

Cryptography is fundamental to the security of modern communications, data storage and confidential computing. This introductory course covers the essential principles, methods and applications of cryptography and gives students a foundation for understanding and applying cryptographic techniques in security contexts.

Topics

  • Classical cryptographic systems
  • Pseudo-random functions (PRF) and permutations (PRP)
  • Block ciphers, including DES and AES
  • Symmetric encryption techniques
  • Message authentication codes (MACs)
  • Authenticated encryption
  • Hash functions
  • Basic group theory concepts
  • Diffie-Hellman key exchange
  • Asymmetric encryption
  • Digital signatures
  • Secure multi-party computation
Course
MEDZ4260
When
Winter semester
Format
Practical course
Lecturers
Mete Akgün, Şeyma Selcan Mağara, Cem Ata Baykara

Secure Processing of Medical Data: Privacy-Enhancing Technologies in Practice

Students gain hands-on experience with privacy-enhancing technologies for medical data and genome processing. Working in teams on mini research projects, they apply state-of-the-art privacy-preserving techniques to computational challenges in medical data analysis, building practical skills and theoretical knowledge in a collaborative setting.

Course components

  • Understanding and implementing privacy-enhancing methods
  • Team projects on real-world medical data privacy problems
  • Short team presentations of results
Course
MEDZ4521
When
Winter semester
Format
Seminar
Lecturers
Mete Akgün, Şeyma Selcan Mağara

Computer Science Methods for Privacy Preservation in Biomedical Studies: Data Privacy

A seminar on contemporary research in data privacy and its applications, including social network privacy, machine learning privacy and biomedical data privacy. Students learn to communicate complex research and to think critically about it.

What students do

  • Read, summarize and present state-of-the-art papers on data privacy
  • Critically assess the contributions of research papers
  • Present research results to peers and lead discussions
  • Evaluate findings in oral presentations and written reports

Looking for a Master's project or thesis? See Master's projects.