alexander.warnecke (at) tu-bs.de (PGP-Key)
+49 531 391-55125
+49 531 391-55130
Technische Universität Braunschweig
Institute of System Security
38106 Braunschweig, Germany
I am a PhD student at the Institute of System Security, TU Braunschweig. Prior to that I graduated from Georg-August-University Göttingen in Mathematics and Computer Science and worked in the R&D department of the Volkswagen Group. My research interests revolve around machine learning techniques for computer security applications, in particular how to explain such systems and enrich them with uncertainty measures.
Machine Unlearning of Features and Labels
Alexander Warnecke, Lukas Pirch, Christian Wressnegger and Konrad Rieck.
Proc. of the 30th Network and Distributed System Security Symposium (NDSS), to appear February 2023.
Dos and Don'ts of Machine Learning in Computer Security.
Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro and Konrad Rieck.
Proc. of the 31st USENIX Security Symposium, August 2022.
Distinguished Paper Award.
TAGVET: Vetting Malware Tags using Explainable Machine Learning.
Lukas Pirch, Alexander Warnecke, Christian Wressnegger and Konrad Rieck.
Proc. of 14th ACM European Workshop on Systems Security (EuroSec), April 2021.
Explaining Graph Neural Networks for Vulnerability Discovery
Tom Ganz, Martin Härterich, Alexander Warnecke and Konrad Rieck.
Proc. of the 14th ACM Workshop on Artificial Intelligence and Security (AISEC), 2021.
Best Paper Award
Evaluating Explanation Methods for Deep Learning in Computer Security.
Alexander Warnecke, Daniel Arp, Christian Wressnegger and Konrad Rieck.
Proc. of the 5th IEEE European Symposium on Security and Privacy (EuroS&P), September 2020.
Convolutional Neural Networks for Movement Prediction in Videos.
Alexander Warnecke, Timo Lüddecke, Florentin Wörgötter.
German Conference on Pattern Recognition (GCPR).
If you are interested in writing your final thesis at our institute do not hesitate to contact me via e-mail. Oftentimes, I have topics available. Below you can find a list of theses I supervised in the past.
|2019||M.Sc.||Graph-Based Malware Detection with Dynamic Analysis|
|2020||B.Sc.||Analysis of Android Malware using Bayesian Networks|
|2020||M.Sc.||Attacking Black-Box Explanation Methods|
|2022||M.Sc.||Explaining differences between machine learning models for Android malware detection using influence functions|
|2022||M.Sc.||Black-Box Attacks for the explanation methods LIME and KernelSHAP|
|2022||M.Sc.||Detection and Explanation of Domain Generation Algorithms|