Hasso-Plattner-Institut25 Jahre HPI
Hasso-Plattner-Institut25 Jahre HPI

Security for the Internet of Things (Sommersemester 2019)

Dozent: Prof. Dr. Christoph Meinel (Internet-Technologien und -Systeme) , Konrad-Felix Krentz (Internet-Technologien und -Systeme)

Allgemeine Information

  • Semesterwochenstunden: 4
  • ECTS: 6
  • Benotet: Ja
  • Einschreibefrist: 2604.2019
  • Lehrform: Seminar / Projekt
  • Belegungsart: Wahlpflichtmodul
  • Lehrsprache: Deutsch
  • Maximale Teilnehmerzahl: 8

Studiengänge, Modulgruppen & Module

IT-Systems Engineering MA
  • IT-Systems Engineering
    • HPI-ITSE-A Analyse
  • IT-Systems Engineering
    • HPI-ITSE-E Entwurf
  • IT-Systems Engineering
    • HPI-ITSE-K Konstruktion
  • IT-Systems Engineering
    • HPI-ITSE-M Maintenance
  • ISAE: Internet, Security & Algorithm Engineering
    • HPI-ISAE-S Spezialisierung
  • ISAE: Internet, Security & Algorithm Engineering
    • HPI-ISAE-T Techniken und Werkzeuge
  • OSIS: Operating Systems & Information Systems Technology
    • HPI-OSIS-K Konzepte und Methoden
  • OSIS: Operating Systems & Information Systems Technology
    • HPI-OSIS-S Spezialisierung
  • OSIS: Operating Systems & Information Systems Technology
    • HPI-OSIS-T Techniken und Werkzeuge
  • ISAE: Internet, Security & Algorithm Engineering
    • HPI-ISAE-K Konzepte und Methoden
Data Engineering MA
Digital Health MA


The Internet of things (IoT) enables fascinating applications, such as smart homes, smart cities, precision agriculture, and industrial automation. Since securing the IoT is of paramount importance, many IoT security solutions were proposed. However, a timely issue is to also improve on security-independent aspects of IoT security solutions, such as usability, reliability, and energy efficiency.

In this year's edition of this seminar, the focus will hence be on improving existing IoT security solutions by complementing them with self-configuration and self-optimization capabilities. Some techniques that may become relevant in this endeavor are:

  • Reinforcement learning
  • Transmission power control
  • PHY key generation
  • Adaptive duty cycling

Lern- und Lehrformen

Students will work in teams of about 2 persons. Each team will choose a specific project to work on. There will be an intermediate presentation, where each team primarily presents related work, and a final presentation, where each team presents its results. Furthermore, each team is supposed to author a paper and create a prototypical implementation.


The final grade will be based on the intermediate presentation, the final presentation, the final paper, as well as the implementation.