PNS: Protection in Networked Systems ‒ Trust, Resilience, and Privacy

PNS: Protection in Networked Systems ‒ Trust, Resilience, and Privacy


Type Time Room Start
Lecture Tue, 13:30 – 15:10 Moodle course (online) 13. Apr. 2021
Exam TBA TBA  

Course objectives

The integrated lecture Protection in Networked Systems ‒ Trust, Resilience, and Privacy covers the topics of computational trust, resilient and anonymous networks, and collaborative defense mechanisms. By attending this course, the students will be able to understand the problems and solutions in the context of networked systems. The course content will consider the concept of End-to-End systems emphasizing on users, devices, networks, and applications or services.

Course content

  • Protection in Networked Systems: background, motivation, challenges
  • Privacy: privacy definitions, models, data anonymity, communication anonymity
  • Trust (Computational Trust): models and mechanisms
  • Security & Economics
  • Resilience: models, network intrusion detection systems, collaborative intrusion detection systems, honeypots
  • Resilient networks: measurement of reslience and dependability, methods to increase resilience in networked systems

This lecture covers important topics which are part of the current research in the collaborative research center CROSSING and GRK-2050.


Knowledge of IT Security and Mathematics according to 1-4 semester of B.Sc. Computer Science

Relevant literature

  • Trust and Reputation for Service-Oriented Environments: Technologies For Building Business Intelligence And Consumer Confidence, Elizabeth Chang, Tharam Dillon, and Farookh K. Hussain, 374 pages, 2006. ISBN: 978-0-470-01547-6
  • Detailing Reviews and Ratings for Trust-Enhanced Composition, Florian Volk, 272 pages, 2015, ISBN: 9783736991668 (print), 9783736981669 (e-book)
  • On anonymity in an electronic society: A survey of anonymous communication systems, Matthew Edman and Bülent Yener, ACM Computing Surveys, Vol. 42, Issue 1, 2009.
  • Taxonomy and Survey of Collaborative Intrusion Detection, Emmanouil Vasilomanolakis, Shankar Karuppayah, Max Mühlhäuser, Mathias Fischer, ACM Computing Surveys, Vol. 47 Issue 4, 2015.
  • Selected book chapters and scientific publications

Teaching Staff

Name Office E-mail
Dr.-Ing. Andrea TundisS2|02 A316
Dr. Shankar KaruppayahS2|02 A313