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Christian Wressnegger
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2020 – today
- 2024
- [j7]Daniel Arp
, Erwin Quiring
Pitfalls in Machine Learning for Computer Security. Commun. ACM 67(11): 104-112 (2024) - [j6]Nurullah Demir, Tobias Urban
A Large-Scale Study of Cookie Banner Interaction Tools and their Impact on Users' Privacy. Proc. Priv. Enhancing Technol. 2024(1): 5-20 (2024) - [c37]Qi Zhao
Adversarially Robust Anti-Backdoor Learning. AISec@CCS 2024: 77-88 - [c36]Maximilian Noppel
A Brief Systematization of Explanation-Aware Attacks. KI 2024: 350-354 - [c35]Maximilian Noppel
SoK: Explainable Machine Learning in Adversarial Environments. SP 2024: 2441-2459 - [e3]Steffen Wendzel, Christian Wressnegger, Laura Hartmann, Felix C. Freiling, Frederik Armknecht, Lena Reinfelder:
Sicherheit, Schutz und Zuverlässigkeit: Konferenzband der 12. Jahrestagung des Fachbereichs Sicherheit der Gesellschaft für Informatik e.V. (GI), Sicherheit 2024, Worms, Germany, April 9-11, 2024. LNI P-345, Gesellschaft für Informatik e.V. 2024, ISBN 978-3-88579-739-5 [contents] - [i11]Karl Rubel, Maximilian Noppel, Christian Wressnegger:
Generalized Adversarial Code-Suggestions: Exploiting Contexts of LLM-based Code-Completion. CoRR abs/2410.10526 (2024) - 2023
- [j5]Daniel Arp
Lessons Learned on Machine Learning for Computer Security. IEEE Secur. Priv. 21(5): 72-77 (2023) - [c34]Maximilian Noppel
Poster: Fooling XAI with Explanation-Aware Backdoors. CCS 2023: 3612-3614 - [c33]Qi Zhao, Christian Wressnegger:
Holistic Adversarially Robust Pruning. ICLR 2023 - [c32]Nurullah Demir, Jan Hörnemann, Matteo Große-Kampmann, Tobias Urban
On the Similarity of Web Measurements Under Different Experimental Setups. IMC 2023: 356-369 - [c31]Nico Weidmann, Thomas Barber
Load-and-Act: Increasing Page Coverage of Web Applications. ISC 2023: 163-182 - [c30]Alexander Warnecke, Lukas Pirch
Machine Unlearning of Features and Labels. NDSS 2023 - [c29]Maximilian Noppel
Disguising Attacks with Explanation-Aware Backdoors. SP 2023: 664-681 - [c28]Yilin Ji, Daniel Kästner, Oliver Wirth, Christian Wressnegger:
Randomness is the Root of All Evil: More Reliable Evaluation of Deep Active Learning. WACV 2023: 3932-3941 - 2022
- [c27]Qi Zhao, Tim Köonigl, Christian Wressnegger:
Non-Uniform Adversarially Robust Pruning. AutoML 2022: 1/1-16 - [c26]Jan Ludwig Reubold, Stephan Escher, Christian Wressnegger, Thorsten Strufe:
to Protect the Public Opinion Against New Types of Bots? IEEE Big Data 2022: 1671-1680 - [c25]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 - [c24]Nurullah Demir
Reproducibility and Replicability of Web Measurement Studies. WWW 2022: 533-544 - [e2]Christian Wressnegger, Delphine Reinhardt, Thomas Barber, Bernhard C. Witt, Daniel Arp, Zoltán Ádám Mann:
Sicherheit, Schutz und Zuverlässigkeit: Konferenzband der 11. Jahrestagung des Fachbereichs Sicherheit der Gesellschaft für Informatik e.V. (GI), Sicherheit 2022, Karlsruhe, Germany, April 5-8, 2022. LNI P-323, Gesellschaft für Informatik e.V. 2022, ISBN 978-3-88579-717-3 [contents] - [i10]Maximilian Noppel, Lukas Peter, Christian Wressnegger:
Backdooring Explainable Machine Learning. CoRR abs/2204.09498 (2022) - 2021
- [c23]Niclas Kühnapfel, Stefan Preußler, Maximilian Noppel
LaserShark: Establishing Fast, Bidirectional Communication into Air-Gapped Systems. ACSAC 2021: 796-811 - [c22]Manoj Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Sreetama Sarkar, Qi Zhao
Adversarial Robust Model Compression Using In-Train Pruning. CVPR Workshops 2021: 66-75 - [c21]Lukas Pirch
TagVet: Vetting Malware Tags using Explainable Machine Learning. EuroSec@EuroSys 2021: 34-40 - [c20]Christiane Kuhn, Maximilian Noppel
Plausible Deniability for Anonymous Communication. WPES@CCS 2021: 17-32 - [i9]Niclas Kühnapfel, Stefan Preußler, Maximilian Noppel, Thomas Schneider, Konrad Rieck, Christian Wressnegger:
LaserShark: Establishing Fast, Bidirectional Communication into Air-Gapped Systems. CoRR abs/2106.04119 (2021) - [i8]Alexander Warnecke, Lukas Pirch, Christian Wressnegger, Konrad Rieck:
Machine Unlearning of Features and Labels. CoRR abs/2108.11577 (2021) - 2020
- [j4]Christian Wressnegger:
Efficient machine learning for attack detection. it Inf. Technol. 62(5-6): 279-286 (2020) - [c19]Tim Witschel, Christian Wressnegger:
Aim low, shoot high: evading aimbot detectors by mimicking user behavior. EuroSec@EuroSys 2020: 19-24 - [c18]Ansgar Kellner, Christian Wressnegger, Konrad Rieck:
What's all that noise: analysis and detection of propaganda on Twitter. EuroSec@EuroSys 2020: 25-30 - [c17]Alexander Warnecke, Daniel Arp, Christian Wressnegger, Konrad Rieck:
Evaluating Explanation Methods for Deep Learning in Security. EuroS&P 2020: 158-174 - [e1]Melanie Volkamer, Christian Wressnegger:
ARES 2020: The 15th International Conference on Availability, Reliability and Security, Virtual Event, Ireland, August 25-28, 2020. ACM 2020, ISBN 978-1-4503-8833-7 [contents] - [i7]Tim Witschel, Christian Wressnegger:
Aim Low, Shoot High: Evading Aimbot Detectors by Mimicking User Behavior. CoRR abs/2004.12183 (2020) - [i6]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
- [b1]Christian Wressnegger:
Efficient Machine Learning for Attack Detection. Braunschweig University of Technology, Germany, 2019 - [c16]Marius Musch, Christian Wressnegger, Martin Johns
Thieves in the Browser: Web-based Cryptojacking in the Wild. ARES 2019: 4:1-4:10 - [c15]Marius Musch, Christian Wressnegger, Martin Johns
New Kid on the Web: A Study on the Prevalence of WebAssembly in the Wild. DIMVA 2019: 23-42 - [c14]Alwin Maier, Hugo Gascon, Christian Wressnegger, Konrad Rieck:
TypeMiner: Recovering Types in Binary Programs Using Machine Learning. DIMVA 2019: 288-308 - [c13]Rouven Scholz, Christian Wressnegger:
Security Analysis of Devolo HomePIug Devices. EuroSec@EuroSys 2019: 7:1-7:6 - [c12]Ansgar Kellner, Micha Horlboge
False Sense of Security: A Study on the Effectivity of Jailbreak Detection in Banking Apps. EuroS&P 2019: 1-14 - [i5]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) - [i4]Ansgar Kellner, Lisa Rangosch, Christian Wressnegger, Konrad Rieck:
Political Elections Under (Social) Fire? Analysis and Detection of Propaganda on Twitter. CoRR abs/1912.04143 (2019) - 2018
- [c11]Christian Wressnegger, Ansgar Kellner, Konrad Rieck:
ZOE: Content-Based Anomaly Detection for Industrial Control Systems. DSN 2018: 127-138 - [i3]Marius Musch, Christian Wressnegger, Martin Johns, Konrad Rieck:
Web-based Cryptojacking in the Wild. CoRR abs/1808.09474 (2018) - [i2]Battista Biggio, Konrad Rieck, Davide Ariu, Christian Wressnegger, Igino Corona, Giorgio Giacinto, Fabio Roli:
Poisoning Behavioral Malware Clustering. CoRR abs/1811.09985 (2018) - 2017
- [j3]Christian Wressnegger, Fabian Yamaguchi, Alwin Maier, Konrad Rieck:
64-Bit Migration Vulnerabilities. it Inf. Technol. 59(2): 73 (2017) - [c10]Christian Wressnegger, Kevin Freeman, Fabian Yamaguchi, Konrad Rieck:
Automatically Inferring Malware Signatures for Anti-Virus Assisted Attacks. AsiaCCS 2017: 587-598 - [c9]Christian Wressnegger, Konrad Rieck:
Looking Back on Three Years of Flash-based Malware. EUROSEC 2017: 6:1-6:6 - [c8]Daniel Arp, Erwin Quiring, Christian Wressnegger, Konrad Rieck:
Privacy Threats through Ultrasonic Side Channels on Mobile Devices. EuroS&P 2017: 35-47 - 2016
- [j2]Konrad Rieck, Christian Wressnegger:
Harry: A Tool for Measuring String Similarity. J. Mach. Learn. Res. 17: 9:1-9:5 (2016) - [c7]Christian Wressnegger, Fabian Yamaguchi, Alwin Maier, Konrad Rieck:
Twice the Bits, Twice the Trouble: Vulnerabilities Induced by Migrating to 64-Bit Platforms. CCS 2016: 541-552 - [c6]Christian Wressnegger, Fabian Yamaguchi, Daniel Arp, Konrad Rieck:
Comprehensive Analysis and Detection of Flash-Based Malware. DIMVA 2016: 101-121 - [i1]Christian Wressnegger, Kevin Freeman, Fabian Yamaguchi, Konrad Rieck:
From Malware Signatures to Anti-Virus Assisted Attacks. CoRR abs/1610.06022 (2016) - 2015
- [c5]Hugo Gascon, Christian Wressnegger, Fabian Yamaguchi, Daniel Arp, Konrad Rieck:
Pulsar: Stateful Black-Box Fuzzing of Proprietary Network Protocols. SecureComm 2015: 330-347 - 2014
- [c4]Battista Biggio
Poisoning behavioral malware clustering. AISec@CCS 2014: 27-36 - 2013
- [c3]Christian Wressnegger, Guido Schwenk, Daniel Arp, Konrad Rieck:
A close look on n-grams in intrusion detection: anomaly detection vs. classification. AISec 2013: 67-76 - [c2]Fabian Yamaguchi, Christian Wressnegger, Hugo Gascon, Konrad Rieck:
Chucky: exposing missing checks in source code for vulnerability discovery. CCS 2013: 499-510 - [c1]Christian Wressnegger, Frank Boldewin, Konrad Rieck:
Deobfuscating Embedded Malware Using Probable-Plaintext Attacks. RAID 2013: 164-183 - 2012
- [j1]Konrad Rieck, Christian Wressnegger, Alexander Bikadorov:
Sally: a tool for embedding strings in vector spaces. J. Mach. Learn. Res. 13: 3247-3251 (2012)
Coauthor Index
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last updated on 2024-12-02 21:32 CET by the dblp team
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