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Thursday, March 2 • 11:00 - 12:30
Data Mining for Security (2)

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A common application of data mining in security is the detection of attacks. Learning methods can often generate detection models that are competitive with manually crafted patterns and reduce the manual effort of analyzing attack data. In this session, we present learning-based detection approaches. We discuss the underlying learning concepts, namely classification and anomaly detection, and look at some practical examples. We close this discussion by pointing at novel problems, such as poisoning and evasion attacks against machine learning.

avatar for Konrad Rieck

Konrad Rieck

Professor, TU Braunschweig
I am a Professor of Computer Science at Technische Universität Braunschweig. I am leading the Institute of System Security. Prior to taking this position, I have been working at the University of Göttingen, Technische Universität Berlin and Fraunhofer Institute FIRST. | | My research interests revolve around computer security and machine learning. This includes the detection of computer attacks, the analysis of malicious software, and the... Read More →

Thursday March 2, 2017 11:00 - 12:30
Room: Lemaire

Attendees (4)