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Machine Learning for Computer Security
General
Semester | Summer 2013 |
Lecturer | Prof. Dr. Konrad Rieck |
Assistant | Fabian Yamaguchi |
Course type | Lecture (UniVZ) |
Module | M.Inf.1224 |
ECTS (SWS) | 6 (4) |
Date | Lecture: Tuesday, 10–12 Exercise: Wednesday, 10–12 |
Location | Lecture: Informatik 2.101 Exercise: Informatik 1.101 |
Start | Lecture: 9.4.2013 Exercise: 10.4.2013 |
Audio recording | yes |
Audience | Applied Computer Science MSc Applied Computer Science BSc ITIS MSc |
Description
The course deals with the combination of machine learning and computer security. Approaches for automatically detecting and analyzing security threats are discussed. Topics include anomaly detection, automatic signature generation, classification and clustering of malicious software.
Topics
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Schedule
- 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
- More references will be announced in each lecture
Date | Topic | Slides | Video | Sheets |
09.04. | Introduction | x | x | |
16.04. | Machine Learning in a Nutshell | x | x | 1 |
23.04. | Feature Spaces and Kernel Functions | x | x | 2 |
30.04. | Tutorial: Numpy, Scipy and Matplotlib | x | x | |
07.05. | Learning-based Intrusion Detection I | x | x | 3 |
14.05. | Learning-based Intrusion Detection II | x | x | 4 |
21.05. | Automatic Signature Generation | x | x | 5 |
28.05. | Clustering of Malicious Software | x | x | 6 |
04.06. | Excursus: Deobfuscating Embedded Malware | x | x | 7 |
11.06. | Vulnerability Discovery using Machine Learning | x | x | 8 |
18.06. | Adversarial Machine Learning (Guest: Dr. Pavel Laskov, University of Tübingen) | x | x | |
25.06. | Privacy Attacks using Machine Learning | x | x | 9 |
02.07. | Closing and Outlook (Theses Topics) | x | ||
09.07. | — written exam — |
Exam
You need to solve 50% of the exercise sheets to take part in the written exam. The exam will take place on the 09.07.2013 from 10.00–12.00 in Room 2.101. You need to register for the exam with FlexNow (or at your Examination Office). The exam will be in English. Please do not bring any additional material to the exam.
Results
MD5 of matriculation number | Grade | Points |
e277742c98c271c3f28a48593a21fa3b | 2.0 | 41.5 |
5f1e7f2c52b14dc48ba6e3a9709cc087 | 2.0 | 41.5 |
a2fa8e335f42aa3581728775a0e8a060 | 1.7 | 42.5 |
ee5cdcffe481a407f3428a7d2c66b05e | 2.3 | 39.5 |
b1313a77d89fae3445785590cc09dc98 | 3.0 | 33.5 |
2682dc0afd84531ecb66d4a44b7f8b14 | 2.0 | 40.0 |
8bc480dbf0a339ef00825e69b779d0a8 | 1.3 | 45.5 |
d40030489375f123bf6e556c719f2ecd | 2.7 | 34.5 |
dc944797f57a8490cdf50dce958f0ff3 | 1.7 | 43.0 |
2080c20764fef945ed691335118e2b56 | 1.0 | 47.5 |
5268e056bf8d521d7e707cf1f79aa023 | 5.0 | 23.0 |
83704c8a2d269ac292f266220d07bcc2 | 2.3 | 39.5 |
3cfe85e06340521fd06ffc15fb8a815b | 3.3 | 30.0 |
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 register for the mailing list here.
IRC Channel
All students of the course are encouraged to join the IRC channel #goesec on EFnet. The channel is used as a platform for discussing and chatting about computer security in a casual atmosphere.