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.
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.
Written exam
The written exam takes place on 31.07. from 08:30-10:00 in room PK 11.3. Do not bring any additional material or electronic devices to the exam, in particular no smartphones, tablets and laptops.
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
