TU BRAUNSCHWEIG

Machine Learning for Computer Security

Overview

Semester: Summer 2017
Course type: Lecture & Exercises,
Lecturer: Prof. Dr. Konrad Rieck
Assistants: Alwin Maier
Audience: Informatik Master, Wirtschaftsinformatik Master
Credits: 5 ECTS
Hours: 2+2
Time: Lecture: Tuesday, 9:45 - 11:15 (Start: 04.04.17)
Exercises: Wednesday, 9:45 - 11:15 (Start: 12.04.17)
Place: Lecture: BRICS 45
Exercises: BRICS 45

Schedule

 Date  Topic  Slides  Sheets
 04.04.  Introduction    
 11.04.  Machine Learning in a Nutshell    
 18.04.  Tutorial: Numpy and Scipy    
 25.04.  Features and Feature Spaces    
 02.05.  Besuch der Nds. Staatskanzlei    
 09.05.  Learning-based Intrusion Detection 1    
 16.05.  Learning-based Intrusion Detection 2    
 23.05.  Deep Learning for Malware Analysis    
 30.05.  Automatic Signature Generation    
 06.06.  No lecture – Excursion week    
 13.06.  Intelligent Vulnerability Discovery    
 20.06.  Clustering Methods for Malware Analysis    
 27.06.  Privacy Attacks using Machine Learning    
 04.07.  Adversarial Machine Learning    
 11.07.  Wrap-Up and Outlook (Theses Topics)    
 28.07.  Written exam 12:00-14:30 in PK 2.1    

Description

The lecture is concerned with the combination of machine learning and computer security. Many tasks in computer security, such as the analysis of malicious software or the discovery of vulnerabilities, largely rest on manual work. A tedious and time-consuming process. Methods from machine learning and data mining can help to accelerate this process and make security systems more 'intelligent'. The lecture explores different approaches for constructing such learning-based security systems.

Mailing List

There is a mailing list for the lecture. News and updates regarding the schedule are posted to this list. Furthermore, the list allows students to discuss topics of the lecture. You can subscribe here.

Contact

The lecture is organized by the Institute of System Security. For questions and further details please contact

Written exam

The written exam takes place on 28.07. from 12:00-14:30 in rooms PK 2.1. Please do not bring any additional material to the exam.

Results

 PIN  Points  Percentage  Grade
 1529  40.00   76.9%  2.3
 1857  51.00   98.1%  1.0
 3726  42.00   80.8%  2.0
 5338  44.50   85.6%  1.7
 6594  42.00   80.8%  2.0
 7363  37.00   71.2%  2.7
 7450  41.50   79.8%  2.3


References

  • Duda, Hart and Stork. Pattern Classification. Wiley & Sons 2001
  • Shawe-Taylor & Cristianini. Kernel Methods for Pattern Analysis. Cambridge 2004
  • Gollmann. Computer Security. Wiley & Sons, 2011
  • Szor. The Art of Computer Virus Research and Defense. Addison-Wesley, 2005
  • Rieck. Machine Learning for Application-Layer Intrusion Detection, Lulu 2009
  • More references will be announced in each lecture

  aktualisiert am 14.08.2017
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