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Intrusion Detection Systems

Intrusion Detection Systems  

Seminare 2 SWS / 5 ECTS
Veranstalter: Mohammad Reza Norouzian
Zeit und Ort:

Preliminary Meeting: Thursday 04 February 2021 / 14 h


The lecture is given in english
The slides are available in english
The exam will be in english


  • The kick-off meeting slide can be found here. If you could not attend the meeting, no problem. You can also apply by sending your short CV to Mohammad Norouzian (norouzian@sec.in.tum.de) and choosing the course on the matching system.
  • Introduction slides can be found here.
  • The deadline for report submission is 09.07.21 via Email.



  • Preliminary Meeting: Thursday, 04.02.2021, 14.00
  • Introductory information: Thursday, 13.04.2021, 14.00



An intrusion detection system (IDS) is a device or software application that monitors a network or system for malicious activity. The most common classification is either in the network (NIDS) or host-based (HIDS) intrusion detection systems, in reference to what is monitored by the IDS. Network-based intrusion detection attempts to identify unauthorized, illicit, and anomalous behavior based solely on network traffic. A network IDS, using either a network tap, span port, or hub collects packets that traverse a given network. Using the captured data, the IDS system processes and flags any suspicious traffic. One approach to classify attacks is using an anomaly detection method based on machine learning algorithms. Students involve reading and writing papers regarding the basis and state-of-the-art of IDS, especially in the anomaly detection domain.


Basics of IT security



The goal for students is to be acquainted with methods, algorithms, and technologies in intrusion detection systems, how to identify malicious activities and how to address the challenges in this domain.


Presentation Schedule

Speaker Topic Date
Mohammad Reza Norouzian Introduction to IDS Seminar 13.04.21
Philipp Stratil
Tobias Bauer
Analyzing and Classifying Encrypted Network Traffic
Advanced Persistent Threats 
Philipp Eisermann
Nguyen Truong An To

Intrusion Detection for SCADA
Attacks for SCADA Infrastructure

Mika Mampe
Simon Hülkenberg
Network Intrusion Detection Systems
Anamoly Detection Methods in Industrial Control Systems
Jasper Ruehl
Pascal Moser
Anomaly Detection: Time Series Analysis
Feature Selection Methods for Intrusion Detection Systems
Aashya Khanduja
Anna Schmitt
Adversarial Machine Learning
Federated Machine Learning on Intrusion Detection


Report and Presentation Guidelines

Students are strongly encouraged to use IEEE Conference Template and IEEE Editorial Style Manual

How to write a seminar report (link)

How to write a great research paper (link)

How to give a great research talk (link)

Avoid making common report writing mistakes: Download the general guidelines

Academic Phrasebank (link)

How to Read a Paper (link)