Pri­va­cy and Tech­no­lo­gy

Course, Master, Every Winter, L.079.05705 

This course will provide students with a basic understanding of privacy risks, the most common technologies to tackle them and the human factors shaping their design. The course will analyze the adversary models and evaluation metrics underlying the design of privacy-enhancing technologies.

Learning outcomes

  • Critical reasoning about privacy

  • Gain knowledge in the evaluation of privacy risks

  • Understand the design aspects of privacy-enhancing technologies

  • Get familiar with the latest research in the field

  • Analyze and discuss the space of solutions to a given privacy problem

Course Topics (no necessarily in order and subject to changes)

  • Motivation

  • Privacy metrics and adversary models

  • Anonymous communications

  • Data-perturbative privacy-enhancing technologies

  • Anonymization algorithms for databases

  • Homomorphic encryption and zero knowledge proofs

  • Selective disclosure for identity management

  • Usable privacy

  • Applying privacy principles and case studies

FURTHER INFORMATION:

TEACHING
RESEARCH
TEAM