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ORCIDAlexander Warnecke
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2020 – today
- 2024
[b1]Alexander Warnecke:
Security viewpoints on explainable machine learning. Technical University of Berlin, Germany, 2024- [j2]Daniel Arp
, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck:
Pitfalls in Machine Learning for Computer Security. Commun. ACM 67(11): 104-112 (2024) - [i5]Dilyara Bareeva, Marina M.-C. Höhne, Alexander Warnecke, Lukas Pirch, Klaus-Robert Müller, Konrad Rieck, Kirill Bykov:
Manipulating Feature Visualizations with Gradient Slingshots. CoRR abs/2401.06122 (2024) - 2023
- [j1]Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck:
Lessons Learned on Machine Learning for Computer Security. IEEE Secur. Priv. 21(5): 72-77 (2023) - [c12]Alexander Warnecke, Lukas Pirch, Christian Wressnegger, Konrad Rieck:
Machine Unlearning of Features and Labels. NDSS 2023 - [i4]Alexander Warnecke, Julian Speith, Jan-Niklas Möller, Konrad Rieck, Christof Paar:
Evil from Within: Machine Learning Backdoors through Hardware Trojans. CoRR abs/2304.08411 (2023) - 2022
- [c11]Nitika Ghosh, Akhil Garg, Alexander Warnecke, Bijaya K. Panigrahi:
State of Health Estimation of Lithium-Ion Batteries for Dynamic Driving Profiles Based on Feature Extraction from Battery Relaxation Time Using Machine Learning. IECON 2022: 1-6 - [c10]Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck:
Dos and Don'ts of Machine Learning in Computer Security. USENIX Security Symposium 2022: 3971-3988 - 2021
- [c9]Tom Ganz, Martin Härterich, Alexander Warnecke, Konrad Rieck:
Explaining Graph Neural Networks for Vulnerability Discovery. AISec@CCS 2021: 145-156 - [c8]Felix Kortmann, Daniel Brieske, Pia Piekarek, Julian Eckstein, Alexander Warnecke, Paul Drews, Dirk Uwe Sauer:
Concept of a Cloud State Modeling System for Lead-Acid Batteries: Theory and Prototyping. ICEIC 2021: 1-4 - [c7]Lukas Pirch, Alexander Warnecke, Christian Wressnegger, Konrad Rieck:
TagVet: Vetting Malware Tags using Explainable Machine Learning. EuroSec@EuroSys 2021: 34-40 - [i3]Alexander Warnecke, Lukas Pirch, Christian Wressnegger, Konrad Rieck:
Machine Unlearning of Features and Labels. CoRR abs/2108.11577 (2021) - 2020
- [c6]Felix Kortmann, Kevin Talits, Pascal Fassmeyer, Alexander Warnecke, Nicolas Meier, Jens Heger, Paul Drews, Burkhardt Funk:
Detecting Various Road Damage Types in Global Countries Utilizing Faster R-CNN. IEEE BigData 2020: 5563-5571 - [c5]Alexander Warnecke, Daniel Arp, Christian Wressnegger, Konrad Rieck:
Evaluating Explanation Methods for Deep Learning in Security. EuroS&P 2020: 158-174 - [c4]Felix Kortmann, Julin Horstkötter, Alexander Warnecke, Nicolas Meier, Jens Heger, Burkhardt Funk, Paul Drews:
Live Demonstration: Passive Sensor Setup for Road Condition Monitoring. IEEE SENSORS 2020: 1 - [c3]Felix Kortmann, Yi-Chen Hsu, Alexander Warnecke, Nicolas Meier, Jens Heger, Burkhardt Funk, Paul Drews:
Creating Value from in-Vehicle Data: Detecting Road Surfaces and Road Hazards. ITSC 2020: 1-6 - [c2]Felix Kortmann, Malte Rodeheger, Alexander Warnecke, Nicolas Meier, Jens Heger, Burkhardt Funk, Paul Drews:
Applying Quarter-Vehicle Model Simulation for Road Elevation Measurements Utilizing the Vehicle Level Sensor. VTC Fall 2020: 1-6 - [i2]Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, Konrad Rieck:
Dos and Don'ts of Machine Learning in Computer Security. CoRR abs/2010.09470 (2020)
2010 – 2019
- 2019
- [i1]Alexander Warnecke, Daniel Arp, Christian Wressnegger, Konrad Rieck:
Don't Paint It Black: White-Box Explanations for Deep Learning in Computer Security. CoRR abs/1906.02108 (2019) - 2017
- [c1]Alexander Warnecke, Timo Lüddecke, Florentin Wörgötter:
Convolutional Neural Networks for Movement Prediction in Videos. GCPR 2017: 215-225
Coauthor Index
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