Publications by Konrad Rieck

2023

Detecting Backdoors in Collaboration Graphs of Software Repositories.
Tom Ganz, Inaam Ashraf, Martin Härterich and Konrad Rieck.
Proc. of the 14th ACM Conference on Data and Applications Security and Privacy (CODASPY), 2023.

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), 2023.

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Improving Malware Detection with Explainable Machine Learning.
Michele Scalas, Konrad Rieck and Giorgio Giacinto.
Explainable Deep Learning AI: Methods and Challenges, Elsevier, 2023.

Möglichkeiten und Grenzen KI-gestützter Analyse digitaler Spuren.
Andreas Dewald, Felix Freiling, Tobias Gross, Dennis Kniel, Robert Michael and Konrad Rieck.
Kriminalistik, Jan, 2023.

Security of Machine Learning.
Battista Biggio, Nicholas Carlini, Pavel Laskov, Konrad Rieck and Antonio Cina.
Technical report, Dagstuhl, 12, (7), 41–61, 2023.

2022

I still know it's you! On Challenges in Anonymizing Source Code.
Micha Horlboge, Erwin Quiring, Roland Meyer and Konrad Rieck.
Technical report, arXiv:2208.12553, 2022.

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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, 2022.
Distinguished Paper Award

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Quantifying the Risk of Wormhole Attacks on Bluetooth Contact Tracing.
Stefan Czybik, Daniel Arp and Konrad Rieck.
Proc. of the 13th ACM Conference on Data and Applications Security and Privacy (CODASPY), 264–275, 2022.

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Misleading Deep-Fake Detection with GAN Fingerprints.
Vera Wesselkamp, Konrad Rieck, Daniel Arp and Erwin Quiring.
Proc. of the 5th IEEE Workshop on Deep Learning and Security (DLS), 2022.

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2021

LaserShark: Establishing Fast, Bidirectional Communication into Air-Gapped Systems.
Niclas Kühnapfel, Stefan Preußler, Maximilian Noppel, Thomas Schneider, Konrad Rieck and Christian Wressnegger.
Proc. of the 37th Annual Computer Security Applications Conference (ACSAC), 2021.

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Spying through Virtual Backgrounds of Video Calls.
Jan Hilgefort, Daniel Arp and Konrad Rieck.
Proc. of the 14th ACM Workshop on Artificial Intelligence and Security (AISEC), 2021.

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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

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Machine Unlearning of Features and Labels.
Alexander Warnecke, Lukas Pirch, Christian Wressnegger and Konrad Rieck.
Technical report, arXiv:2108.11577, 2021.

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LogPicker: Strengthening Certificate Transparency Against Covert Adversaries.
Alexandra Dirksen, David Klein, Robert Michael, Tilman Stehr, Konrad Rieck and Martin Johns.
Proceedings on Privacy Enhancing Technologies (PETS), 2021.

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TagVet: Vetting Malware Tags using Explainable Machine Learning.
Lukas Pirch, Alexander Warnecke, Christian Wressnegger and Konrad Rieck.
Proc. of the 14th ACM European Workshop on Systems Security (EuroSec), 2021.

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2020

Explanation-driven Characterisation of Android Ransomware.
Michele Scalas, Konrad Rieck and Giorgio Giacinto.
Proc. of Workshop on Explainable Deep Learning/AI, 2020.

Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification.
Erwin Quiring, Lukas Pirch, Michael Reimsbach, Daniel Arp and Konrad Rieck.
Technical report, arXiv:2010.09569, 2020.

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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, 2020.

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Evaluating Explanation Methods for Deep Learning in Security.
Alexander Warnecke, Daniel Arp, Christian Wressnegger and Konrad Rieck.
Proc. of the 5th IEEE European Symposium on Security and Privacy (EuroS&P), 2020.

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Adversarial Preprocessing: Understanding and Preventing Image-Scaling Attacks in Machine Learning.
Erwin Quiring, David Klein, Daniel Arp, Martin Johns and Konrad Rieck.
Proc. of the 29th USENIX Security Symposium, 2020.

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Backdooring and Poisoning Neural Networks with Image-Scaling Attacks.
Erwin Quiring and Konrad Rieck.
Proc. of the 3rd IEEE Workshop on Deep Learning and Security (DLS), 2020.

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What's All That Noise: Analysis and Detection of Propaganda on Twitter.
Ansgar Kellner, Christian Wressnegger and Konrad Rieck.
Proc. of the 13th ACM European Workshop on Systems Security (EuroSec), 2020.

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2019

Political Elections Under (Social) Fire? Analysis and Detection of Propaganda on Twitter.
Ansgar Kellner, Lisa Rangosch, Christian Wressnegger and Konrad Rieck.
Technical report, arXiv:1912.04143, 2019.

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Evaluating Explanation Methods for Deep Learning in Security.
Alexander Warnecke, Daniel Arp, Christian Wressnegger and Konrad Rieck.
Technical report, arXiv:1906.02108, 2019.

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On the Security and Applicability of Fragile Camera Fingerprints.
Erwin Quiring, Matthias Kirchner and Konrad Rieck.
Proc. of the 24th European Symposium on Research in Computer Security (ESORICS), 450–470, 2019.

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Misleading Authorship Attribution of Source Code using Adversarial Learning.
Erwin Quiring, Alwin Maier and Konrad Rieck.
Proc. of the 28th USENIX Security Symposium, 2019.

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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), 2019.
Best Paper Award Runner-Up

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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 the 16th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 23–42, 2019.
Best Paper Award Runner-Up

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TypeMiner: Recovering Types in Binary Programs using Machine Learning.
Alwin Maier, Hugo Gascon, Christian Wressnegger and Konrad Rieck.
Proc. of the 16th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 288–308, 2019.

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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 the 4th IEEE European Symposium on Security and Privacy (EuroS&P), 2019.

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2nd IEEE Deep Learning and Security Workshop (DLS).
Konrad Rieck and Battista Biggio (Ed.).
Workshop proceedings, IEEE, 2019.

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12th ACM European Workshop on Systems Security (EuroSec).
Konrad Rieck and Lorenzo Cavallaro (Ed.).
Workshop proceedings, ACM, 2019.

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2018

Adversarial Machine Learning Against Digital Watermarking.
Erwin Quiring and Konrad Rieck.
Proc. of the 26th European Signal Processing Conference (EUSIPCO), 2018.

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Reading Between The Lines: Content-Agnostic Detection of Spear-Phishing Emails.
Hugo Gascon, Steffen Ullrich, Benjamin Stritter and Konrad Rieck.
Proc. of the 21st Symposium on Research in Attacks, Intrusions, and Defenses (RAID), 2018.

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Web-based Cryptojacking in the Wild.
Marius Musch, Christian Wressnegger, Martin Johns and Konrad Rieck.
Technical report, arXiv:1808.09474, 2018.

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Privacy-Enhanced Fraud Detection with Bloom filters.
Daniel Arp, Erwin Quiring, Tammo Krueger, Stanimir Dragiev and Konrad Rieck.
Proc. of the 14th International Conference on Security and Privacy in Communication Networks (SECURECOMM), 2018.

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ZOE: Content-based Anomaly Detection for Industrial Control Systems.
Christian Wressnegger, Ansgar Kellner and Konrad Rieck.
Proc. of the 48th Conference on Dependable Systems and Networks (DSN), 127–138, 2018.

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11th ACM European Workshop on Systems Security (EuroSec).
Angelos Stavrou and Konrad Rieck (Ed.).
Workshop proceedings, ACM, 2018.

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Forgotten Siblings: Unifying Attacks on Machine Learning and Digital Watermarking.
Erwin Quiring, Daniel Arp and Konrad Rieck.
Proc. of the 3rd IEEE European Symposium on Security and Privacy (EuroS&P), 2018.

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When Coding Style Survives Compilation: De-anonymizing Programmers from Executable Binaries.
Aylin Caliskan, Fabian Yamaguchi, Edwin Tauber, Richard Harang, Konrad Rieck, Rachel Greenstadt and Arvind Narayanan.
Proc. of the 25th Network and Distributed System Security Symposium (NDSS), 2018.

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2017

Static Program Analysis as a Fuzzing Aid.
Bhargava Shastry, Markus Leutner, Tobias Fiebig, Kashyap Thimmaraju, Fabian Yamaguchi, Konrad Rieck, Stefan Schmid, Jean-Pierre Seifert and Anja Feldmann.
Proc. of the 20th Symposium on Research in Attacks, Intrusions, and Defenses (RAID), 2017.

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Leveraging Flawed Tutorials for Seeding Large-Scale Web Vulnerability Discovery.
Tommi Unruh, Bhargava Shastry, Malte Skoruppa, Federico Maggi, Konrad Rieck, Jean-Pierre Seifert and Fabian Yamaguchi.
Proc. of the USENIX Workshop on Offensive Technologies (WOOT), 2017.

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Static Exploration of Taint-Style Vulnerabilities Found by Fuzzing.
Bhargava Shastry, Federico Maggi, Fabian Yamaguchi, Konrad Rieck and Jean-Pierre Seifert.
Proc. of the USENIX Workshop on Offensive Technologies (WOOT), 2017.

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Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection.
Ambra Demontis, Marco Melis, Battista Biggio, Davide Maiorca, Daniel Arp, Konrad Rieck, Igino Corona, Giorgio Giacinto and Fabio Roli.
IEEE Transactions on Dependable and Secure Computing (TDSC), 2017.

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64-bit Migration Vulnerabilities.
Christian Wressnegger, Fabian Yamaguchi, Alwin Maier and Konrad Rieck.
Information Technology (IT), 59, (2), 73–82, De Gruyter, 2017.

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Looking Back on Three Years of Flash-based Malware.
Christian Wressnegger and Konrad Rieck.
Proc. of the 10th ACM European Workshop on Systems Security (EuroSec), 2017.

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Automatically Inferring Malware Signatures for Anti-Virus Assisted Attacks.
Christian Wressnegger, Kevin Freeman, Fabian Yamaguchi and Konrad Rieck.
Proc. of the ACM Asia Conference on Computer and Communications Security (ASIACCS), 587–598, 2017.

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Special Issue on Vulnerability Analysis.
Konrad Rieck.
Information Technology (IT), 59, (2), 57–58, De Gruyter, 2017.

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TrustJS: Trusted Client-side Execution of JavaScript.
David Goltzsche, Colin Wulf, Divya Muthukumaran, Konrad Rieck, Peter Pietzuch and Rüdiger Kapitza.
Proc. of the 10th ACM European Workshop on Systems Security (EuroSec), 2017.

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Efficient and Flexible Discovery of PHP Application Vulnerabilities.
Michael Backes, Konrad Rieck, Malte Skoruppa, Ben Stock and Fabian Yamaguchi.
Proc. of the 2nd IEEE European Symposium on Security and Privacy (EuroS&P), 2017.

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Privacy Threats through Ultrasonic Side Channels on Mobile Devices.
Daniel Arp, Erwin Quiring, Christian Wressnegger and Konrad Rieck.
Proc. of the 2nd IEEE European Symposium on Security and Privacy (EuroS&P), 35–47, 2017.

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Fraternal Twins: Unifying Attacks on Machine Learning and Digital Watermarking.
Erwin Quiring, Daniel Arp and Konrad Rieck.
Technical report, arXiv:1703.05561, 2017.

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Mining Attributed Graphs for Threat Intelligence.
Hugo Gascon, Bernd Grobauer, Thomas Schreck, Lukas Rist, Daniel Arp and Konrad Rieck.
Proc. of the 8th ACM Conference on Data and Applications Security and Privacy (CODASPY), 15–22, 2017.

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2016

Die Codeanalyseplattform “Octopus”.
Fabian Yamaguchi and Konrad Rieck.
Datenschutz und Datensicherheit (DuD), 40, (11), 713–717, 2016.

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 the 23rd ACM Conference on Computer and Communications Security (CCS), 541–552, 2016.

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From Malware Signatures to Anti-Virus Assisted Attacks.
Christian Wressnegger, Kevin Freeman, Fabian Yamaguchi and Konrad Rieck.
Technical report, Technische Universität Braunschweig, (2016-03), 2016.

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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), 2016.

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Comprehensive Analysis and Detection of Flash-based Malware.
Christian Wressnegger, Fabian Yamaguchi, Daniel Arp and Konrad Rieck.
Proc. of the 13th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 101–121, 2016.
Best Paper Award

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Towards Vulnerability Discovery Using Staged Program Analysis.
Bhargava Shastry, Fabian Yamaguchi, Konrad Rieck and Jean-Pierre Seifert.
Proc. of the 13th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 78–97, 2016.

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Monte Carlo Localization for Path-Based Mobility in Mobile Wireless Sensor Networks.
Salke Hartung, Ansgar Kellner, Konrad Rieck and Dieter Hogrefe.
Proc. of the 18th IEEE Wireless Communications and Networking Conference (WCNC), 1–7, 2016.

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Harry: A Tool for Measuring String Similarity.
Konrad Rieck and Christian Wressnegger.
Journal of Machine Learning Research (JMLR), 17, (9), 1–5, 2016.

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2015

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), 2015.

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When Coding Style Survives Compilation: De-anonymizing Programmers from Executable Binaries.
Aylin Caliskan, Fabian Yamaguchi, Edwin Dauber, Richard Harang, Konrad Rieck, Rachel Greenstadt and Arvind Narayanan.
Technical report, arXiv:1512.08546, 2015.

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VCCFinder: Finding Potential Vulnerabilities in Open-Source Projects to Assist Code Audits.
Henning Perl, Daniel Arp, Sergej Dechand, Sascha Fahl, Yasemin Acar, Fabian Yamaguchi, Konrad Rieck and Matthew Smith.
Proc. of the 22nd ACM Conference on Computer and Communications Security (CCS), 2015.

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Pulsar: Stateful Black-Box Fuzzing of Proprietary Network Protocols.
Hugo Gascon, Christian Wressnegger, Fabian Yamaguchi, Daniel Arp and Konrad Rieck.
Proc. of the 11th International Conference on Security and Privacy in Communication Networks (SECURECOMM), 330–347, 2015.

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Fingerprinting Mobile Devices Using Personalized Configurations.
Andreas Kurtz, Hugo Gascon, Tobias Becker, Konrad Rieck and Felix Freiling.
Proceedings on Privacy Enhancing Technologies (PETS), 2016, (1), 4–19, 2015.

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Automatic Inference of Search Patterns for Taint-Style Vulnerabilities.
Fabian Yamaguchi, Alwin Maier, Hugo Gascon and Konrad Rieck.
Proc. of the 36th IEEE Symposium on Security and Privacy (S&P), 2015.

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Torben: A Practical Side-Channel Attack for Deanonymizing Tor Communication.
Daniel Arp, Fabian Yamaguchi and Konrad Rieck.
Proc. of the 10th ACM Symposium on Information, Computer and Communications Security (ASIACCS), 2015.

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2014

Torben: Deanonymizing Tor Communication using Web Page Markers.
Daniel Arp, Fabian Yamaguchi and Konrad Rieck.
Technical report, University of Göttingen, (IFI-TB-2014-01), 2014.

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Poisoning Behavioral Malware Clustering.
Battista Biggio, Konrad Rieck, Davide Ariu, Christian Wressnegger, Igino Corona, Giorgio Giacinto and Fabio Roli.
Proc. of the 7th ACM Workshop on Artificial Intelligence and Security (AISEC), 1–10, 2014.

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Special Issue on Threat Detection, Analysis and Defense.
Shujun Li, Konrad Rieck and Alan Woodward.
Journal of Information Security and Applications (JISA), 19, (3), 163–164, 2014.

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Modeling and Discovering Vulnerabilities with Code Property Graphs.
Fabian Yamaguchi, Nico Golde, Daniel Arp and Konrad Rieck.
Proc. of the 35th IEEE Symposium on Security and Privacy (S&P), 2014.

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Continuous Authentication on Mobile Devices by Analysis of Typing Motion Behavior.
Hugo Gascon, Sebastian Uellenbeck, Christopher Wolf and Konrad Rieck.
Proc. of the GI Conference “Sicherheit, Schutz und Zuverlässigkeit” (SICHERHEIT), 2014.

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Drebin: Efficient and Explainable Detection of Android Malware in Your Pocket.
Daniel Arp, Michael Spreitzenbarth, Malte Hübner, Hugo Gascon and Konrad Rieck.
Proc. of the 21st Network and Distributed System Security Symposium (NDSS), 2014.

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2013

Chucky: Exposing Missing Checks in Source Code for Vulnerability Discovery.
Fabian Yamaguchi, Christian Wressnegger, Hugo Gascon, Charles Ray and Konrad Rieck.
Proc. of the 20th ACM Conference on Computer and Communications Security (CCS), 499–510, 2013.

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A Close Look on n-Grams in Intrusion Detection: Anomaly Detection vs. Classification.
Christian Wressnegger, Guido Schwenk, Daniel Arp and Konrad Rieck.
Proc. of the 6th ACM Workshop on Artificial Intelligence and Security (AISEC), 67–76, 2013.

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Off the Beaten Path: Machine Learning for Offensive Security.
Konrad Rieck.
Proc. of the 6th ACM Workshop on Artificial Intelligence and Security (AISEC), 1–2, 2013.

Structural Detection of Android Malware using Embedded Call Graphs.
Hugo Gascon, Fabian Yamaguchi, Daniel Arp and Konrad Rieck.
Proc. of the 6th ACM Workshop on Artificial Intelligence and Security (AISEC), 45–54, 2013.

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Deobfuscating Embedded Malware using Probable-Plaintext Attacks.
Christian Wressnegger, Frank Boldewin and Konrad Rieck.
Proc. of the 16th Symposium on Research in Attacks, Intrusions, and Defenses (RAID), 164–183, 2013.

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Drebin: Efficient and Explainable Detection of Android Malware in Your Pocket.
Daniel Arp, Michael Spreitzenbarth, Malte Hübner, Hugo Gascon and Konrad Rieck.
Technical report, University of Göttingen, (IFI-TB-2013-02), 2013.

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10th Conference on Detection of Intrusions and Malware & Vulnerability Assessment.
Konrad Rieck, Patrick Stewin and Jean-Pierre Seifert (Ed.).
Conference proceedings, Springer, 2013.

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Toward Supervised Anomaly Detection.
Nico Görnitz, Marius Kloft, Konrad Rieck and Ulf Brefeld.
Journal of Artificial Intelligence Research (JAIR), 46, (1), 235–262, 2013.

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2012

Generalized Vulnerability Extrapolation using Abstract Syntax Trees.
Fabian Yamaguchi, Markus Lottmann and Konrad Rieck.
Proc. of the 28th Annual Computer Security Applications Conference (ACSAC), 359–368, 2012.
Outstanding Paper Award

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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, 2012.

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Autonomous Learning for Detection of JavaScript Attacks: Vision or Reality?
Guido Schwenk, Alexander Bikadorov, Tammo Krueger and Konrad Rieck.
Proc. of the 5th ACM Workshop on Artificial Intelligence and Security (AISEC), 93–104, 2012.

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Early Detection of Malicious Behavior in JavaScript Code.
Kristof Schütt, Alexander Bikadorov, Marius Kloft and Konrad Rieck.
Proc. of the 5th ACM Workshop on Artificial Intelligence and Security (AISEC), 15–24, 2012.

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Learning Stateful Models for Network Honeypots.
Tammo Krueger, Hugo Gascon, Nicole Kraemer and Konrad Rieck.
Proc. of the 5th ACM Workshop on Artificial Intelligence and Security (AISEC), 37–48, 2012.

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Intelligent Defense against Malicious JavaScript Code.
Tammo Krueger and Konrad Rieck.
Praxis der Informationsverarbeitung und Kommunikation (PIK), 35, (1), 54–60, 2012.

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Support Vector Machines.
Konrad Rieck, Sören Sonnenburg, Sebastian Mika, Christian Schäfer, Pavel Laskov, David Tax and Klaus-Robert Müller.
Handbook of Computational Statistics, 883–926, Springer, 2012.

2011

Smart Metering De-Pseudonymization.
Marek Jawurek, Martin Johns and Konrad Rieck.
Proc. of the 27th Annual Computer Security Applications Conference (ACSAC), 227–236, 2011.

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Adaptive Detection of Covert Communication in HTTP Requests.
Guido Schwenk and Konrad Rieck.
Proc. of the 7th European Conference on Network Defense (EC2ND), 25–32, 2011.

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Vulnerability Extrapolation: Assisted Discovery of Vulnerabilities using Machine Learning.
Fabian Yamaguchi, Felix Lindner and Konrad Rieck.
Proc. of the USENIX Workshop on Offensive Technologies (WOOT), 118–127, 2011.

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Computer Security and Machine Learning: Worst Enemies or Best Friends?
Konrad Rieck.
Proc. of the 1st Workshop on Systems Security (SYSSEC), 107–110, 2011.

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Similarity Measures for Sequential Data.
Konrad Rieck.
WIREs: Data Mining and Knowledge Discovery, 1, (4), 296–304, Wiley, 2011.

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Automatic Analysis of Malware Behavior using Machine Learning.
Konrad Rieck, Philipp Trinius, Carsten Willems and Thorsten Holz.
Journal of Computer Security (JCS), 19, (4), 639–668, IOSPress, 2011.

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Self-Learning Network Intrusion Detection.
Konrad Rieck.
Information Technology (IT), 53, (3), 152–156, Oldenbourg, 2011.

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2010

Cujo: Efficient Detection and Prevention of Drive-by-Download Attacks.
Konrad Rieck, Tammo Krueger and Andreas Dewald.
Proc. of the 26th Annual Computer Security Applications Conference (ACSAC), 31–39, 2010.

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6th European Conference on Computer Network Defense.
Konrad Rieck (Ed.).
Conference proceedings, IEEE Computer Society, 2010.

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A Malware Instruction Set for Behavior-based Analysis.
Philipp Trinius, Carsten Willems, Thorsten Holz and Konrad Rieck.
Proc. of the GI Conference “Sicherheit, Schutz und Zuverlässigkeit” (SICHERHEIT), 205–216, 2010.

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ASAP: Automatic Semantics-Aware Analysis of Network Payloads.
Tammo Krueger, Nicole Kraemer and Konrad Rieck.
Proc. of the ECML Workshop on Privacy and Security Issues in Machine Learning, 50–63, 2010.

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Cujo: Efficient Detection and Prevention of Drive-by-Download Attacks.
Konrad Rieck, Tammo Krueger and Andreas Dewald.
Technical report, Technische Universität Berlin, (2010-10), 2010.

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Botzilla: Detecting the “Phoning Home” of Malicious Software.
Konrad Rieck, Guido Schwenk, Tobias Limmer, Thorsten Holz and Pavel Laskov.
Proc. of the 25th ACM Symposium on Applied Computing (SAC), 1978–1984, 2010.

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TokDoc: A Self-Healing Web Application Firewall.
Tammo Krueger, Christian Gehl, Konrad Rieck and Pavel Laskov.
Proc. of the 25th ACM Symposium on Applied Computing (SAC), 1846–1853, 2010.

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FIPS: FIRST Intrusion Prevention System.
Ingmar Schuster, Tammo Krueger, Christian Gehl, Konrad Rieck and Pavel Laskov.
Technical report, Fraunhofer Institute FIRST, (FIRST 1/2010), 2010.

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Approximate Tree Kernels.
Konrad Rieck, Tammo Krueger, Ulf Brefeld and Klaus-Robert Müller.
Journal of Machine Learning Research (JMLR), 11, (Feb), 555–580, Microtome, 2010.

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2009

A Malware Instruction Set for Behavior-Based Analysis.
Philipp Trinius, Carsten Willems, Thorsten Holz and Konrad Rieck3.
Technical report, University of Mannheim, (TR-2009-07), 2009.

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Automatic Analysis of Malware Behavior using Machine Learning.
Konrad Rieck, Philipp Trinius, Carsten Willems and Thorsten Holz.
Technical report, Technische Universität Berlin, (2009-18), 2009.

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Visualization and Explanation of Payload-Based Anomaly Detection.
Konrad Rieck and Pavel Laskov.
Proc. of the 5th European Conference on Network Defense (EC2ND), 2009.

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Active Learning for Network Intrusion Detection.
Nico Görnitz, Marius Kloft, Konrad Rieck and Ulf Brefeld.
Proc. of the 2nd ACM Workshop on Artificial Intelligence and Security (AISEC), 47–54, 2009.

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Securing IMS against Novel Threats.
Stefan Wahl, Konrad Rieck, Pavel Laskov, Peter Domschitz and Klaus-Robert Müller.
Bell Labs Technical Journal, 14, (1), 243–257, Wiley, 2009.

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2008

An Architecture for Inline Anomaly Detection.
Tammo Krueger, Christian Gehl, Konrad Rieck and Pavel Laskov.
Proc. of the 4th European Conference on Network Defense (EC2ND), 11–18, 2008.

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Incorporation of Application Layer Protocol Syntax into Anomaly Detection.
Patrick Düssel, Christian Gehl, Pavel Laskov and Konrad Rieck..
Proc. of the 4th International Conference on Information Systems Security (ICISS), 188–202, 2008.

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Approximate Kernels for Trees.
Konrad Rieck, Ulf Brefeld and Tammo Krueger.
Technical report, Fraunhofer Institute FIRST, (FIRST 5/2008), 2008.

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Machine Learning for Intrusion Detection.
Pavel Laskov, Konrad Rieck and Klaus-Robert Müller.
Mining Massive Data Sets for Security, 366–373, IOS press, 2008.

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A Self-Learning System for Detection of Anomalous SIP Messages.
Konrad Rieck, Stefan Wahl, Pavel Laskov, Peter Domschitz and Klaus-Robert Müller.
Principles, Systems and Applications of IP Telecommunications (IPTCOMM), 90–106, 2008.

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Learning and Classification of Malware Behavior.
Konrad Rieck, Thorsten Holz, Carsten Willems, Patrick Düssel and Pavel Laskov.
Proc. of the 5th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 108–125, 2008.

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Attack Taxonomy.
Marc Dacier, Herve Debar, Thorsten Holz, Engin Kirda, Jan Kohlrausch, Christopher Kruegel, Konrad Rieck and James Sterbenz.
Perspectives Workshop: Network Attack Detection and Defense (Dagstuhl Proceedings), 2008.

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Requirements for Network Monitoring from an IDS Perspective.
Lothar Braun, Falko Dressler, Thorsten Holz, Engin Kirda, Jan Kohlrausch, Christopher Kruegel, Tobias Limmer, Konrad Rieck and James Sterbenz.
Perspectives Workshop: Network Attack Detection and Defense (Dagstuhl Proceedings), 2008.

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Measuring and Detecting Fast-Flux Service Networks.
Thorsten Holz, Christian Gorecki, Konrad Rieck and Felix Freiling.
Proc. of the 15th Network and Distributed System Security Symposium (NDSS), 2008.

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Linear-Time Computation of Similarity Measures for Sequential Data.
Konrad Rieck and Pavel Laskov.
Journal of Machine Learning Research (JMLR), 9, (Jan), 23–48, Microtome, 2008.

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2007

Computation of Similarity Measures for Sequential Data using Generalized Suffix Trees.
Konrad Rieck, Pavel Laskov and Sören Sonnenburg.
Advances in Neural Information Processing Systems (NeurIPS), 2007.

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Large scale learning with string kernels.
Sören Sonnenburg, Gunnar Rätsch and Konrad Rieck.
Large Scale Kernel Machines, 73–103, MIT Press, 2007.

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Language Models for Detection of Unknown Attacks in Network Traffic.
Konrad Rieck and Pavel Laskov.
Journal in Computer Virology (JICV), 2, (4), 243–256, Springer, 2007.

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2006

Efficient Algorithms for Similarity Measures over Sequential Data: A Look beyond Kernels.
Konrad Rieck, Pavel Laskov and Klaus-Robert Müller.
Proc. of the DAGM Symposium on Pattern Recognition, 374–383, 2006.

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Detecting Unknown Network Attacks using Language Models.
Konrad Rieck and Pavel Laskov.
Proc. of the 3rd Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 74–90, 2006.

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2005

Learning intrusion detection: supervised or unsupervised?
Pavel Laskov, Patrick Düssel, Christin Schäfer and Konrad Rieck.
Proc. of the 13th International Conference on Image Analysis and Processing (ICIAP), 50–57, 2005.

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Visualization of anomaly detection using prediction sensitivity.
Pavel Laskov, Konrad Rieck, Christin Schäfer and Klaus-Robert Müller.
Proc. of the GI Conference “Sicherheit, Schutz und Zuverlässigkeit” (SICHERHEIT), 197–208, 2005.

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