DUMPLING: Fine-grained Differential JavaScript Engine Fuzzing.
Liam Wachter, Julian Gremminger, Christian Wressnegger, Mathias Payer and Flavio Toffalini.
Proc. of 32nd Network and Distributed System Security Symposium (NDSS), February 2025.
Model-Manipulation Attacks Against Black-Box Explanations.
Achyut Hegde, Maximilian Noppel and Christian Wressnegger.
Proc. of 40th Annual Computer Security Applications Conference (ACSAC), December 2024.
Adversarially Robust Anti-Backdoor Learning.
Qi Zhao and Christian Wressnegger.
Proc. of 17th ACM Workshop on Artificial Intelligence and Security (AISEC), October 2024.
A Brief Systematization of Explanation-Aware Attacks.
Maximilian Noppel and Christian Wressnegger.
Proc. of 47th German Conference on Artificial Intelligence, September 2024.
A Large-Scale Study of Cookie Banner Interaction Tools and their Impact on Users' Privacy.
Nurullah Demir, Tobias Urban, Norbert Pohlmann and Christian Wressnegger.
Proc. of Privacy Enhancing Technologies Symposium (PETS), July 2024.
SoK: Explainable Machine Learning in Adversarial Environments.
Maximilian Noppel and Christian Wressnegger.
Proc. of 45th IEEE Symposium on Security and Privacy (S&P), May 2024.
Proc. of "Jahrestagung des Fachbereichs Sicherheit der Gesellschaft für Informatik" (GI SICHERHEIT).
Steffen Wendzel, Christian Wressnegger, Laura Hartmann, Felix Freiling, Federik Armknecht and Lena Reinfelder (Eds.).
GI, April 2024.
Poster: Fooling XAI with Explanation-Aware Backdoors.
Maximilian Noppel and Christian Wressnegger.
Proc. of 30th ACM Conference on Computer and Communications Security (CCS), November 2023.
Load-and-Act: Increasing Page Coverage of Web Applications.
Nico Weidmann, Thomas Barber and Christian Wressnegger.
Proc. of 26th Information Security Conference (ISC), November 2023.
On the Similarity of Web Measurements Under Different Experimental Setups.
Nurullah Demir, Jan Hörnemann, Matteo Große-Kampmann, Tobias Urban, Norbert Pohlmann, Thorsten Holz and Christian Wressnegger.
Proc. of 23rd ACM Internet Measurement Conference (IMC), October 2023.
Lessons Learned on Machine Learning for Computer Security.
Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro and Konrad Rieck.
IEEE Security & Privacy, 21 (5), September 2023.
Explanation-Aware Backdoors in a Nutshell.
Maximilian Noppel and Christian Wressnegger.
Proc. of 46th German Conference on Artificial Intelligence, September 2023.
Disguising Attacks with Explanation-Aware Backdoors.
Maximilian Noppel, Lukas Peter and Christian Wressnegger.
Proc. of 44th IEEE Symposium on Security and Privacy (S&P), May 2023.
Holistic Adversarially Robust Pruning.
Qi Zhao and Christian Wressnegger.
Proc. of 11th International Conference on Learning Representations (ICLR), May 2023.
Machine Unlearning of Features and Labels.
Alexander Warnecke, Lukas Pirch, Christian Wressnegger and Konrad Rieck.
Proc. of 30th Network and Distributed System Security Symposium (NDSS), February 2023.
Randomness is the Root of All Evil: More Reliable Evaluation of Deep Active Learning.
Yilin Ji, Daniel Kaestner, Oliver Wirth and Christian Wressnegger.
Proc. of 10th IEEE Winter Conference on Applications of Computer Vision (WACV), January 2023.
How to Protect the Public Opinion Against New Types of Bots?.
Jan Reubold, Stephan Escher, Christian Wressnegger and Thorsten Strufe.
Proc. of 10th IEEE International Conference on Big Data, December 2022.
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 31st USENIX Security Symposium, August 2022.
Distinguished Paper Award
Non-Uniform Adversarially Robust Pruning.
Qi Zhao, Tim Königl and Christian Wressnegger.
Proc. of 1st International Conference on Automated Machine Learning (AutoML), July 2022.
Reproducibility and Replicability of Web Measurement Studies.
Nurullah Demir, Matteo Große-Kampmann, Tobias Urban, Christian Wressnegger, Thorsten Holz and Norbert Pohlmann.
Proc. of 31st ACM Web Conference (WWW), April 2022.
Best Paper Award Runner-Up
Backdooring Explainable Machine Learning.
Maximilian Noppel, Lukas Peter and Christian Wressnegger.
Technical report, arXiv:2204.09498, April 2022.
Proc. of "Jahrestagung des Fachbereichs Sicherheit der Gesellschaft für Informatik" (GI SICHERHEIT).
Christian Wressnegger, Delphine Reinhardt, Thomas Barber, Bernhard Witt, Daniel Arp and Zoltan Mann (Eds.).
GI, April 2022.
LaserShark: Establishing Fast, Bidirectional Communication into Air-Gapped Systems.
Niclas Kühnapfel, Stefan Preußler, Maximilian Noppel, Thomas Schneider, Konrad Rieck and Christian Wressnegger.
Proc. of 37th Annual Computer Security Applications Conference (ACSAC), December 2021.
Plausible Deniability for Anonymous Communication.
Christiane Kuhn, Maximilian Noppel, Christian Wressnegger and Thorsten Strufe.
Proc. of 21st Workshop on Privacy in the Electronic Society (WPES), November 2021.
Machine Unlearning of Features and Labels.
Alexander Warnecke, Lukas Pirch, Christian Wressnegger and Konrad Rieck.
Technical report, arXiv:2108.11577, August 2021.
Poster: Adversarial Robust Model Compression using In-Train Pruning.
Manoj Vemparala, Nael Fasfous, Alexander Frickenstein, Sreetama Sarkar, Qi Zhao, Sabine Kuhn, Lukas Frickenstein, Anmol Singh, Christian Unger, Naveen Nagaraja, Christian Wressnegger and Walter Stechele.
2nd Women in Machine Learning Un-Workshop (WiML), July 2021.
Adversarial Robust Model Compression using In-Train Pruning.
Manoj Vemparala, Nael Fasfous, Alexander Frickenstein, Sreetama Sarkar, Qi Zhao, Sabine Kuhn, Lukas Frickenstein, Anmol Singh, Christian Unger, Naveen Nagaraja, Christian Wressnegger and Walter Stechele.
Proc. of 3rd CVPR Workshop on Safe Artificial Intelligence for Automated Driving (SAIAD), June 2021.
Best Paper Award Runner-Up
TagVet: Vetting Malware Tags using Explainable Machine Learning.
Lukas Pirch, Alexander Warnecke, Christian Wressnegger and Konrad Rieck.
Proc. of 14th European Workshop on System Security (EUROSEC), April 2021.
Efficient Machine Learning for Attack Detection.
Christian Wressnegger.
Information Technology (IT), 63 (2), 73–82, De Gruyter, November 2020.
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.
Technical report, arXiv:2010.09470, October 2020.
Evaluating Explanation Methods for Deep Learning in Security.
Alexander Warnecke, Daniel Arp, Christian Wressnegger and Konrad Rieck.
Proc. of 5th IEEE European Symposium on Security and Privacy (EuroS&P), September 2020.
Proc. of the International Conference on Availability, Reliability and Security (ARES).
Melanie Volkamer and Christian Wressnegger (Ed.).
ACM, August 2020.
What’s All That Noise: Analysis and Detection of Propaganda on Twitter.
Ansgar Kellner, Christian Wressnegger and Konrad Rieck.
Proc. of 13th European Workshop on System Security (EUROSEC), April 2020.
Aim Low, Shoot High: Evading Aimbot Detectors by Mimicking User Behavior.
Tim Witschel and Christian Wressnegger.
Proc. of 13th European Workshop on System Security (EUROSEC), April 2020.
Thieves in the Browser: Web-based Cryptojacking in the Wild.
Marius Musch, Christian Wressnegger, Martin Johns and Konrad Rieck.
Proc. of 14th International Conference on Availability, Reliability and Security (ARES), August 2019.
Best Paper Award Runner-Up
False Sense of Security: A Study on the Effectivity of Jailbreak Detection in Banking Apps.
Ansgar Kellner, Micha Horlboge, Konrad Rieck and Christian Wressnegger.
Proc. of 4th IEEE European Symposium on Security and Privacy (EuroS&P), June 2019.
TypeMiner: Recovering Types in Binary Programs using Machine Learning.
Alwin Maier, Hugo Gascon, Christian Wressnegger and Konrad Rieck.
Proc. of 16th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 288–308, June 2019.
New Kid on the Web: A Study on the Prevalence of WebAssembly in the Wild.
Marius Musch, Christian Wressnegger, Martin Johns and Konrad Rieck.
Proc. of 16th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 23–42, June 2019.
Best Paper Award Runner-Up
Don't Paint It Black: White-Box Explanations for Deep Learning in Computer Security.
Alexander Warnecke, Daniel Arp, Christian Wressnegger and Konrad Rieck.
Technical report, arXiv:1906.02108, June 2019.
Security Analysis of Devolo HomePlug Devices.
Rouven Scholz and Christian Wressnegger.
Proc. of 12th European Workshop on System Security (EUROSEC), March 2019.
Web-based Cryptojacking in the Wild.
Marius Musch, Christian Wressnegger, Martin Johns and Konrad Rieck.
Technical report, arXiv:1808.09474, August 2018.
ZOE: Content-based Anomaly Detection for Industrial Control Systems.
Christian Wressnegger, Ansgar Kellner and Konrad Rieck.
Proc. of 48th Conference on Dependable Systems and Networks (DSN), 127–138, June 2018.
64-bit Migration Vulnerabilities.
Christian Wressnegger, Fabian Yamaguchi, Alwin Maier and Konrad Rieck.
Information Technology (IT), 59 (2), 73–82, De Gruyter, April 2017.
Privacy Threats through Ultrasonic Side Channels on Mobile Devices.
Daniel Arp, Erwin Quiring, Christian Wressnegger and Konrad Rieck.
Proc. of 2nd IEEE European Symposium on Security and Privacy (EuroS&P), 35–47, April 2017.
Looking Back on Three Years of Flash-based Malware.
Christian Wressnegger and Konrad Rieck.
Proc. of 10th European Workshop on System Security (EUROSEC), April 2017.
Automatically Inferring Malware Signatures for Anti-Virus Assisted Attacks.
Christian Wressnegger, Kevin Freeman, Fabian Yamaguchi and Konrad Rieck.
Proc. of 12th ACM Asia Conference on Computer and Communications Security (ASIA CCS), 587–598, April 2017.
Twice the Bits, Twice the Trouble: Vulnerabilities Induced by Migrating to 64-Bit Platforms.
Christian Wressnegger, Fabian Yamaguchi, Alwin Maier and Konrad Rieck.
Proc. of 23rd ACM Conference on Computer and Communications Security (CCS), 541–552, October 2016.
From Malware Signatures to Anti-Virus Assisted Attacks.
Christian Wressnegger, Kevin Freeman, Fabian Yamaguchi and Konrad Rieck.
Technical report, Technische Universität Braunschweig, (2016-03), October 2016.
Bat in the Mobile: A Study on Ultrasonic Device Tracking.
Daniel Arp, Erwin Quiring, Christian Wressnegger and Konrad Rieck.
Technical report, Technische Universität Braunschweig, (2016-02), September 2016.
Comprehensive Analysis and Detection of Flash-based Malware.
Christian Wressnegger, Fabian Yamaguchi, Daniel Arp and Konrad Rieck.
Proc. of 13th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 101–121, July 2016.
Best Paper Award
Harry: A Tool for Measuring String Similarity.
Konrad Rieck and Christian Wressnegger.
Journal of Machine Learning Research (JMLR), 17 (9), 1–5, March 2016.
Analyzing and Detecting Flash-based Malware using Lightweight Multi-Path Exploration.
Christian Wressnegger, Fabian Yamaguchi, Daniel Arp and Konrad Rieck.
Technical report, University of Göttingen, (IFI-TB-2015-05), December 2015.
Pulsar: Stateful Black-Box Fuzzing of Proprietary Network Protocols.
Hugo Gascon, Christian Wressnegger, Fabian Yamaguchi, Daniel Arp and Konrad Rieck.
Proc. of 11th Int. Conference on Security and Privacy in Communication Networks (SECURECOMM), 330–347, October 2015.
Poisoning Behavioral Malware Clustering.
Battista Biggio, Konrad Rieck, Davide Ariu, Christian Wressnegger, Igino Corona, Giorgio Giacinto and Fabio Roli.
Proc. of 7th ACM Workshop on Artificial Intelligence and Security (AISEC), 1–10, November 2014.
A Close Look on n-Grams in Intrusion Detection: Anomaly Detection vs. Classification.
Christian Wressnegger, Guido Schwenk, Daniel Arp and Konrad Rieck.
Proc. of 6th ACM Workshop on Artificial Intelligence and Security (AISEC), 67–76, November 2013.
Chucky: Exposing Missing Checks in Source Code for Vulnerability Discovery.
Fabian Yamaguchi, Christian Wressnegger, Hugo Gascon and Konrad Rieck.
Proc. of 20th ACM Conference on Computer and Communications Security (CCS), 499–510, November 2013.
Deobfuscating Embedded Malware using Probable-Plaintext Attacks.
Christian Wressnegger, Frank Boldewin and Konrad Rieck.
Proc. of 16th International Symposium on Research in Attacks, Intrusions and Defenses (RAID), 164–183, October 2013.
Sally: A Tool for Embedding Strings in Vector Spaces.
Konrad Rieck, Christian Wressnegger and Alexander Bikadorov.
Journal of Machine Learning Research (JMLR), 13 (Nov), 3247–3251, November 2012.