TU BRAUNSCHWEIG

Machine Learning for Computer Security

Overview

Semester: Summer 2016
Course type: Lecture & Exercises,
Lecturer: Prof. Dr. Konrad Rieck
Assistants: Dr. Fabian Yamaguchi
Audience: Informatik Master, Wirtschaftsinformatik Master
Credits: 5 ECTS
Hours: 2+2
Time: Lecture: Tuesday, 15:00 - 16:30
Exercises: Wednesday, 13:15 - 14:45
Place: Lecture: BRICS 45
Exercises: BRICS 45

Schedule

 Date  Topic  Slides  Sheets
 12.04.  Introduction    
 19.04.  Machine Learning in a Nutshell    
 26.04.  Tutorial: Scipy and R    
 03.05.  Features and Feature Spaces    
 10.05.  Learning-based Intrusion Detection 1    
 17.05.  No lecture – Excursion week    
 24.05.  Learning-based Intrusion Detection 2    
 31.05.  Automatic Signature Generation    
 07.06.  Clustering Methods for Malware Analysis    
 14.06.  Deep Learning for Malware Analysis    
 21.06.  Pattern-based Vulnerability Discovery    
 28.06.  Privacy Attacks using Machine Learning    
 05.07.  Wrap-Up and Outlook (Theses Topics)    
 12.07.  Written exam (Room BRICS 45/46)    

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 new established Institute of System Security. For questions and further details please contact

Written exam

The written exam takes place on 12.07.2016 from 15:00-17:00 in room BRICS 45/46. Please do not bring any additional material to the exam.

Results


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 22.06.2017
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