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ORCIDKonrad Rieck
Person information
- affiliation: TU Berlin, Germany
- affiliation (former): TU Braunschweig, Institute of System Security, Germany
- affiliation (former): University of Göttingen, Institute of Computer Science, Germany
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2020 – today
- 2024
[i29]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
- [j19]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) - [c86]Erwin Quiring, Andreas Müller, Konrad Rieck:
On the Detection of Image-Scaling Attacks in Machine Learning. ACSAC 2023: 506-520 - [c85]Tom Ganz, Erik Imgrund, Martin Härterich, Konrad Rieck:
PAVUDI: Patch-based Vulnerability Discovery using Machine Learning. ACSAC 2023: 704-717 - [c84]Konrad Rieck:
When Papers Choose Their Reviewers: Adversarial Machine Learning in Peer Review. ARTMAN@CCS 2023: 3 - [c83]Erik Imgrund, Tom Ganz, Martin Härterich, Lukas Pirch, Niklas Risse, Konrad Rieck:
Broken Promises: Measuring Confounding Effects in Learning-based Vulnerability Discovery. AISec@CCS 2023: 149-160 - [c82]Tom Ganz, Inaam Ashraf, Martin Härterich, Konrad Rieck:
Detecting Backdoors in Collaboration Graphs of Software Repositories. CODASPY 2023: 189-200 - [c81]Tom Ganz, Erik Imgrund, Martin Härterich, Konrad Rieck:
CodeGraphSMOTE - Data Augmentation for Vulnerability Discovery. DBSec 2023: 282-301 - [c80]Lukas Seidel, Sedick David Baker Effendi, Xavier Pinho, Konrad Rieck, Brink van der Merwe, Fabian Yamaguchi:
Learning Type Inference for Enhanced Dataflow Analysis. ESORICS (4) 2023: 184-203 - [c79]Tom Ganz, Philipp Rall, Martin Härterich, Konrad Rieck:
Hunting for Truth: Analyzing Explanation Methods in Learning-based Vulnerability Discovery. EuroS&P 2023: 524-541 - [c78]Stefan Czybik, Micha Horlboge, Konrad Rieck:
Lazy Gatekeepers: A Large-Scale Study on SPF Configuration in the Wild. IMC 2023: 344-355 - [c77]Alexander Warnecke, Lukas Pirch, Christian Wressnegger, Konrad Rieck:
Machine Unlearning of Features and Labels. NDSS 2023 - [c76]Thorsten Eisenhofer, Erwin Quiring, Jonas Möller, Doreen Riepel, Thorsten Holz, Konrad Rieck:
No more Reviewer #2: Subverting Automatic Paper-Reviewer Assignment using Adversarial Learning. USENIX Security Symposium 2023: 5109-5126 - [i28]Thorsten Eisenhofer, Erwin Quiring, Jonas Möller, Doreen Riepel, Thorsten Holz, Konrad Rieck:
No more Reviewer #2: Subverting Automatic Paper-Reviewer Assignment using Adversarial Learning. CoRR abs/2303.14443 (2023) - [i27]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) - [i26]Lukas Seidel, Sedick David Baker Effendi, Xavier Pinho, Konrad Rieck, Brink van der Merwe, Fabian Yamaguchi:
Learning Type Inference for Enhanced Dataflow Analysis. CoRR abs/2310.00673 (2023) - [i25]Erwin Quiring, Andreas Müller, Konrad Rieck:
On the Detection of Image-Scaling Attacks in Machine Learning. CoRR abs/2310.15085 (2023) - 2022
- [c75]Stefan Czybik, Daniel Arp, Konrad Rieck:
Quantifying the Risk of Wormhole Attacks on Bluetooth Contact Tracing. CODASPY 2022: 264-275 - [c74]Vera Wesselkamp, Konrad Rieck, Daniel Arp, Erwin Quiring:
Misleading Deep-Fake Detection with GAN Fingerprints. SP (Workshops) 2022: 59-65 - [c73]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 - [i24]Vera Wesselkamp, Konrad Rieck, Daniel Arp, Erwin Quiring:
Misleading Deep-Fake Detection with GAN Fingerprints. CoRR abs/2205.12543 (2022) - [i23]Micha Horlboge, Erwin Quiring, Roland Meyer, Konrad Rieck:
I still know it's you! On Challenges in Anonymizing Source Code. CoRR abs/2208.12553 (2022) - [i22]Battista Biggio, Nicholas Carlini, Pavel Laskov, Konrad Rieck, Antonio Emanuele Cinà:
Security of Machine Learning (Dagstuhl Seminar 22281). Dagstuhl Reports 12(7): 41-61 (2022) - 2021
- [j18]Alexandra Dirksen, David Klein, Robert Michael, Tilman Stehr, Konrad Rieck, Martin Johns:
LogPicker: Strengthening Certificate Transparency Against Covert Adversaries. Proc. Priv. Enhancing Technol. 2021(4): 184-202 (2021) - [c72]Niclas Kühnapfel, Stefan Preußler, Maximilian Noppel, Thomas Schneider, Konrad Rieck, Christian Wressnegger:
LaserShark: Establishing Fast, Bidirectional Communication into Air-Gapped Systems. ACSAC 2021: 796-811 - [c71]Jan Malte Hilgefort, Daniel Arp, Konrad Rieck:
Spying through Virtual Backgrounds of Video Calls. AISec@CCS 2021: 135-144 - [c70]Tom Ganz, Martin Härterich, Alexander Warnecke, Konrad Rieck:
Explaining Graph Neural Networks for Vulnerability Discovery. AISec@CCS 2021: 145-156 - [c69]Lukas Pirch, Alexander Warnecke, Christian Wressnegger, Konrad Rieck:
TagVet: Vetting Malware Tags using Explainable Machine Learning. EuroSec@EuroSys 2021: 34-40 - [i21]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) - [i20]Alexander Warnecke, Lukas Pirch, Christian Wressnegger, Konrad Rieck:
Machine Unlearning of Features and Labels. CoRR abs/2108.11577 (2021) - [i19]André Noll Barreto, Stefan Köpsell, Arsenia Chorti, Bertram Poettering, Jens Jelitto, Julia Hesse, Jonathan Boole, Konrad Rieck, Marios Kountouris, Dave Singelée, Kumar Ashwinee:
Towards Intelligent Context-Aware 6G Security. CoRR abs/2112.09411 (2021) - 2020
- [c68]Ansgar Kellner, Christian Wressnegger, Konrad Rieck:
What's all that noise: analysis and detection of propaganda on Twitter. EuroSec@EuroSys 2020: 25-30 - [c67]Alexander Warnecke, Daniel Arp, Christian Wressnegger, Konrad Rieck:
Evaluating Explanation Methods for Deep Learning in Security. EuroS&P 2020: 158-174 - [c66]Michele Scalas, Konrad Rieck, Giorgio Giacinto:
Explanation-Driven Characterization of Android Ransomware. ICPR Workshops (3) 2020: 228-242 - [c65]Erwin Quiring, Konrad Rieck:
Backdooring and Poisoning Neural Networks with Image-Scaling Attacks. SP (Workshops) 2020: 41-47 - [c64]Erwin Quiring, David Klein, Daniel Arp, Martin Johns, Konrad Rieck:
Adversarial Preprocessing: Understanding and Preventing Image-Scaling Attacks in Machine Learning. USENIX Security Symposium 2020: 1363-1380 - [i18]Erwin Quiring, Konrad Rieck:
Backdooring and Poisoning Neural Networks with Image-Scaling Attacks. CoRR abs/2003.08633 (2020) - [i17]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) - [i16]Erwin Quiring, Lukas Pirch, Michael Reimsbach, Daniel Arp, Konrad Rieck:
Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification. CoRR abs/2010.09569 (2020)
2010 – 2019
- 2019
- [j17]Ambra Demontis, Marco Melis, Battista Biggio, Davide Maiorca, Daniel Arp, Konrad Rieck, Igino Corona, Giorgio Giacinto, Fabio Roli:
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection. IEEE Trans. Dependable Secur. Comput. 16(4): 711-724 (2019) - [c63]Marius Musch, Christian Wressnegger, Martin Johns, Konrad Rieck:
Thieves in the Browser: Web-based Cryptojacking in the Wild. ARES 2019: 4:1-4:10 - [c62]Marius Musch, Christian Wressnegger, Martin Johns, Konrad Rieck:
New Kid on the Web: A Study on the Prevalence of WebAssembly in the Wild. DIMVA 2019: 23-42 - [c61]Alwin Maier, Hugo Gascon, Christian Wressnegger, Konrad Rieck:
TypeMiner: Recovering Types in Binary Programs Using Machine Learning. DIMVA 2019: 288-308 - [c60]Erwin Quiring, Matthias Kirchner, Konrad Rieck:
On the Security and Applicability of Fragile Camera Fingerprints. ESORICS (1) 2019: 450-470 - [c59]Ansgar Kellner, Micha Horlboge, Konrad Rieck, Christian Wressnegger:
False Sense of Security: A Study on the Effectivity of Jailbreak Detection in Banking Apps. EuroS&P 2019: 1-14 - [c58]Erwin Quiring, Alwin Maier, Konrad Rieck:
Misleading Authorship Attribution of Source Code using Adversarial Learning. USENIX Security Symposium 2019: 479-496 - [i15]Erwin Quiring, Alwin Maier, Konrad Rieck:
Misleading Authorship Attribution of Source Code using Adversarial Learning. CoRR abs/1905.12386 (2019) - [i14]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) - [i13]Erwin Quiring, Matthias Kirchner, Konrad Rieck:
On the Security and Applicability of Fragile Camera Fingerprints. CoRR abs/1907.04025 (2019) - [i12]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
- [c57]Konrad Rieck:
Family Reunion: Adversarial Machine Learning meets Digital Watermarking. MPS@CCS 2018: 1 - [c56]Christian Wressnegger, Ansgar Kellner, Konrad Rieck:
ZOE: Content-Based Anomaly Detection for Industrial Control Systems. DSN 2018: 127-138 - [c55]Erwin Quiring, Daniel Arp, Konrad Rieck:
Forgotten Siblings: Unifying Attacks on Machine Learning and Digital Watermarking. EuroS&P 2018: 488-502 - [c54]Erwin Quiring, Konrad Rieck:
Adversarial Machine Learning Against Digital Watermarking. EUSIPCO 2018: 519-523 - [c53]Aylin Caliskan, Fabian Yamaguchi, Edwin Dauber, Richard E. Harang, Konrad Rieck, Rachel Greenstadt, Arvind Narayanan:
When Coding Style Survives Compilation: De-anonymizing Programmers from Executable Binaries. NDSS 2018 - [c52]Hugo Gascon, Steffen Ullrich, Benjamin Stritter, Konrad Rieck:
Reading Between the Lines: Content-Agnostic Detection of Spear-Phishing Emails. RAID 2018: 69-91 - [c51]Daniel Arp, Erwin Quiring, Tammo Krueger, Stanimir Dragiev, Konrad Rieck:
Privacy-Enhanced Fraud Detection with Bloom Filters. SecureComm (1) 2018: 396-415 - [e2]Angelos Stavrou, Konrad Rieck:
Proceedings of the 11th European Workshop on Systems Security, EuroSec@EuroSys 2018, Porto, Portugal, April 23, 2018. ACM 2018 [contents] - [i11]Marius Musch, Christian Wressnegger, Martin Johns, Konrad Rieck:
Web-based Cryptojacking in the Wild. CoRR abs/1808.09474 (2018) - [i10]Battista Biggio, Konrad Rieck, Davide Ariu, Christian Wressnegger, Igino Corona, Giorgio Giacinto, Fabio Roli:
Poisoning Behavioral Malware Clustering. CoRR abs/1811.09985 (2018) - 2017
- [j16]Konrad Rieck:
Vulnerability analysis. it Inf. Technol. 59(2): 57 (2017) - [j15]Christian Wressnegger, Fabian Yamaguchi, Alwin Maier, Konrad Rieck:
64-Bit Migration Vulnerabilities. it Inf. Technol. 59(2): 73 (2017) - [c50]Christian Wressnegger, Kevin Freeman, Fabian Yamaguchi, Konrad Rieck:
Automatically Inferring Malware Signatures for Anti-Virus Assisted Attacks. AsiaCCS 2017: 587-598 - [c49]Hugo Gascon, Bernd Grobauer, Thomas Schreck, Lukas Rist, Daniel Arp, Konrad Rieck:
Mining Attributed Graphs for Threat Intelligence. CODASPY 2017: 15-22 - [c48]Christian Wressnegger, Konrad Rieck:
Looking Back on Three Years of Flash-based Malware. EUROSEC 2017: 6:1-6:6 - [c47]David Goltzsche, Colin Wulf, Divya Muthukumaran, Konrad Rieck, Peter R. Pietzuch, Rüdiger Kapitza:
TrustJS: Trusted Client-side Execution of JavaScript. EUROSEC 2017: 7:1-7:6 - [c46]Daniel Arp, Erwin Quiring, Christian Wressnegger, Konrad Rieck:
Privacy Threats through Ultrasonic Side Channels on Mobile Devices. EuroS&P 2017: 35-47 - [c45]Michael Backes, Konrad Rieck, Malte Skoruppa, Ben Stock, Fabian Yamaguchi:
Efficient and Flexible Discovery of PHP Application Vulnerabilities. EuroS&P 2017: 334-349 - [c44]Bhargava Shastry, Markus Leutner, Tobias Fiebig, Kashyap Thimmaraju, Fabian Yamaguchi, Konrad Rieck, Stefan Schmid, Jean-Pierre Seifert, Anja Feldmann:
Static Program Analysis as a Fuzzing Aid. RAID 2017: 26-47 - [c43]Bhargava Shastry, Federico Maggi, Fabian Yamaguchi, Konrad Rieck, Jean-Pierre Seifert:
Static Exploration of Taint-Style Vulnerabilities Found by Fuzzing. WOOT 2017 - [c42]Tommi Unruh, Bhargava Shastry, Malte Skoruppa, Federico Maggi, Konrad Rieck, Jean-Pierre Seifert, Fabian Yamaguchi:
Leveraging Flawed Tutorials for Seeding Large-Scale Web Vulnerability Discovery. WOOT 2017 - [i9]Erwin Quiring, Daniel Arp, Konrad Rieck:
Fraternal Twins: Unifying Attacks on Machine Learning and Digital Watermarking. CoRR abs/1703.05561 (2017) - [i8]Tommi Unruh, Bhargava Shastry, Malte Skoruppa, Federico Maggi, Konrad Rieck, Jean-Pierre Seifert, Fabian Yamaguchi:
Leveraging Flawed Tutorials for Seeding Large-Scale Web Vulnerability Discovery. CoRR abs/1704.02786 (2017) - [i7]Ambra Demontis, Marco Melis, Battista Biggio, Davide Maiorca, Daniel Arp, Konrad Rieck, Igino Corona, Giorgio Giacinto, Fabio Roli:
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection. CoRR abs/1704.08996 (2017) - [i6]Bhargava Shastry, Federico Maggi, Fabian Yamaguchi, Konrad Rieck, Jean-Pierre Seifert:
Static Exploration of Taint-Style Vulnerabilities Found by Fuzzing. CoRR abs/1706.00206 (2017) - 2016
- [j14]Fabian Yamaguchi, Konrad Rieck:
Die Codeanalyseplattform "Octopus". Datenschutz und Datensicherheit 40(11): 713-717 (2016) - [j13]Konrad Rieck, Christian Wressnegger:
Harry: A Tool for Measuring String Similarity. J. Mach. Learn. Res. 17: 9:1-9:5 (2016) - [j12]Andreas Kurtz, Hugo Gascon, Tobias Becker, Konrad Rieck, Felix C. Freiling:
Fingerprinting Mobile Devices Using Personalized Configurations. Proc. Priv. Enhancing Technol. 2016(1): 4-19 (2016) - [c41]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 - [c40]Bhargava Shastry, Fabian Yamaguchi, Konrad Rieck, Jean-Pierre Seifert:
Towards Vulnerability Discovery Using Staged Program Analysis. DIMVA 2016: 78-97 - [c39]Christian Wressnegger, Fabian Yamaguchi, Daniel Arp, Konrad Rieck:
Comprehensive Analysis and Detection of Flash-Based Malware. DIMVA 2016: 101-121 - [c38]Salke Hartung, Ansgar Kellner, Konrad Rieck, Dieter Hogrefe:
Monte Carlo Localization for path-based mobility in mobile wireless sensor networks. WCNC 2016: 1-7 - [i5]Christian Wressnegger, Kevin Freeman, Fabian Yamaguchi, Konrad Rieck:
From Malware Signatures to Anti-Virus Assisted Attacks. CoRR abs/1610.06022 (2016) - 2015
- [c37]Henning Perl, Sergej Dechand, Matthew Smith, Daniel Arp, Fabian Yamaguchi, Konrad Rieck, Sascha Fahl, Yasemin Acar:
VCCFinder: Finding Potential Vulnerabilities in Open-Source Projects to Assist Code Audits. CCS 2015: 426-437 - [c36]Daniel Arp, Fabian Yamaguchi, Konrad Rieck:
Torben: A Practical Side-Channel Attack for Deanonymizing Tor Communication. AsiaCCS 2015: 597-602 - [c35]Hugo Gascon, Christian Wressnegger, Fabian Yamaguchi, Daniel Arp, Konrad Rieck:
Pulsar: Stateful Black-Box Fuzzing of Proprietary Network Protocols. SecureComm 2015: 330-347 - [c34]Fabian Yamaguchi, Alwin Maier, Hugo Gascon, Konrad Rieck:
Automatic Inference of Search Patterns for Taint-Style Vulnerabilities. IEEE Symposium on Security and Privacy 2015: 797-812 - [i4]Aylin Caliskan Islam, Fabian Yamaguchi, Edwin Dauber, Richard E. Harang, Konrad Rieck, Rachel Greenstadt, Arvind Narayanan:
When Coding Style Survives Compilation: De-anonymizing Programmers from Executable Binaries. CoRR abs/1512.08546 (2015) - 2014
- [j11]Shujun Li, Konrad Rieck, Alan Woodward:
Special issue on threat detection, analysis and defense. J. Inf. Secur. Appl. 19(3): 163-164 (2014) - [c33]Battista Biggio, Konrad Rieck, Davide Ariu, Christian Wressnegger, Igino Corona, Giorgio Giacinto, Fabio Roli:
Poisoning behavioral malware clustering. AISec@CCS 2014: 27-36 - [c32]Daniel Arp, Michael Spreitzenbarth, Malte Hubner, Hugo Gascon, Konrad Rieck:
DREBIN: Effective and Explainable Detection of Android Malware in Your Pocket. NDSS 2014 - [c31]Hugo Gascon, Sebastian Uellenbeck, Christopher Wolf, Konrad Rieck:
Continuous Authentication on Mobile Devices by Analysis of Typing Motion Behavior. Sicherheit 2014: 1-12 - [c30]Fabian Yamaguchi, Nico Golde, Daniel Arp, Konrad Rieck:
Modeling and Discovering Vulnerabilities with Code Property Graphs. IEEE Symposium on Security and Privacy 2014: 590-604 - [i3]Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf Brefeld:
Toward Supervised Anomaly Detection. CoRR abs/1401.6424 (2014) - 2013
- [j10]Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf Brefeld:
Toward Supervised Anomaly Detection. J. Artif. Intell. Res. 46: 235-262 (2013) - [c29]Konrad Rieck:
Off the beaten path: machine learning for offensive security. AISec 2013: 1-2 - [c28]Hugo Gascon, Fabian Yamaguchi, Daniel Arp, Konrad Rieck:
Structural detection of android malware using embedded call graphs. AISec 2013: 45-54 - [c27]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 - [c26]Fabian Yamaguchi, Christian Wressnegger, Hugo Gascon, Konrad Rieck:
Chucky: exposing missing checks in source code for vulnerability discovery. CCS 2013: 499-510 - [c25]Christian Wressnegger, Frank Boldewin, Konrad Rieck:
Deobfuscating Embedded Malware Using Probable-Plaintext Attacks. RAID 2013: 164-183 - [e1]Konrad Rieck, Patrick Stewin, Jean-Pierre Seifert:
Detection of Intrusions and Malware, and Vulnerability Assessment - 10th International Conference, DIMVA 2013, Berlin, Germany, July 18-19, 2013. Proceedings. Lecture Notes in Computer Science 7967, Springer 2013, ISBN 978-3-642-39234-4 [contents] - 2012
- [j9]Konrad Rieck, Christian Wressnegger, Alexander Bikadorov:
Sally: a tool for embedding strings in vector spaces. J. Mach. Learn. Res. 13: 3247-3251 (2012) - [j8]Tammo Krueger, Konrad Rieck:
Intelligent Defense against Malicious JavaScript Code. Prax. Inf.verarb. Kommun. 35(1): 54-60 (2012) - [c24]Fabian Yamaguchi, Markus Lottmann, Konrad Rieck:
Generalized vulnerability extrapolation using abstract syntax trees. ACSAC 2012: 359-368 - [c23]Kristof Schütt, Marius Kloft, Alexander Bikadorov, Konrad Rieck:
Early detection of malicious behavior in JavaScript code. AISec 2012: 15-24 - [c22]Tammo Krueger, Hugo Gascon, Nicole Krämer, Konrad Rieck:
Learning stateful models for network honeypots. AISec 2012: 37-48 - [c21]Guido Schwenk, Alexander Bikadorov, Tammo Krueger, Konrad Rieck:
Autonomous learning for detection of JavaScript attacks: vision or reality? AISec 2012: 93-104 - 2011
- [j7]Konrad Rieck:
Self-Learning Network Intrusion Detection. it Inf. Technol. 53(3): 152-156 (2011) - [j6]Konrad Rieck, Philipp Trinius, Carsten Willems, Thorsten Holz:
Automatic analysis of malware behavior using machine learning. J. Comput. Secur. 19(4): 639-668 (2011) - [j5]Konrad Rieck:
Similarity measures for sequential data. WIREs Data Mining Knowl. Discov. 1(4): 296-304 (2011) - [c20]Marek Jawurek, Martin Johns, Konrad Rieck:
Smart metering de-pseudonymization. ACSAC 2011: 227-236 - [c19]Konrad Rieck:
Computer Security and Machine Learning: Worst Enemies or Best Friends? SysSec@DIMVA 2011: 107-110 - [c18]Guido Schwenk, Konrad Rieck:
Adaptive Detection of Covert Communication in HTTP Requests. EC2ND 2011: 25-32 - [c17]Fabian Yamaguchi, Felix "FX" Lindner, Konrad Rieck:
Vulnerability Extrapolation: Assisted Discovery of Vulnerabilities Using Machine Learning. WOOT 2011: 118-127 - 2010
- [j4]Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Robert Müller:
Approximate Tree Kernels. J. Mach. Learn. Res. 11: 555-580 (2010) - [c16]Konrad Rieck, Tammo Krueger, Andreas Dewald:
Cujo: efficient detection and prevention of drive-by-download attacks. ACSAC 2010: 31-39 - [c15]Tammo Krueger, Nicole Krämer, Konrad Rieck:
ASAP: Automatic Semantics-Aware Analysis of Network Payloads. PSDML 2010: 50-63 - [c14]Tammo Krueger, Christian Gehl, Konrad Rieck, Pavel Laskov:
TokDoc: a self-healing web application firewall. SAC 2010: 1846-1853 - [c13]Konrad Rieck, Guido Schwenk, Tobias Limmer, Thorsten Holz, Pavel Laskov:
Botzilla: detecting the "phoning home" of malicious software. SAC 2010: 1978-1984 - [c12]Philipp Trinius, Carsten Willems, Thorsten Holz, Konrad Rieck:
A Malware Instruction Set for Behavior-Based Analysis. Sicherheit 2010: 205-216
2000 – 2009
- 2009
- [b1]Konrad Rieck:
Machine learning for application layer intrusion detection. Berlin Institute of Technology, 2009 - [j3]Stefan Wahl, Konrad Rieck, Pavel Laskov, Peter Domschitz, Klaus-Robert Müller:
Securing IMS against novel threats. Bell Labs Tech. J. 14(1): 243-257 (2009) - [c11]Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf Brefeld:
Active learning for network intrusion detection. AISec 2009: 47-54 - 2008
- [j2]Konrad Rieck, Pavel Laskov:
Linear-Time Computation of Similarity Measures for Sequential Data. J. Mach. Learn. Res. 9: 23-48 (2008) - [c10]Konrad Rieck, Thorsten Holz, Carsten Willems, Patrick Düssel, Pavel Laskov:
Learning and Classification of Malware Behavior. DIMVA 2008: 108-125 - [c9]Patrick Düssel, Christian Gehl, Pavel Laskov, Konrad Rieck:
Incorporation of Application Layer Protocol Syntax into Anomaly Detection. ICISS 2008: 188-202 - [c8]Konrad Rieck, Stefan Wahl, Pavel Laskov, Peter Domschitz, Klaus-Robert Müller:
A Self-learning System for Detection of Anomalous SIP Messages. IPTComm 2008: 90-106 - [c7]Thorsten Holz, Christian Gorecki, Konrad Rieck, Felix C. Freiling:
Measuring and Detecting Fast-Flux Service Networks. NDSS 2008 - [i2]Lothar Braun, Falko Dressler, Thorsten Holz, Engin Kirda, Jan Kohlrausch, Christopher Kruegel, Tobias Limmer, Konrad Rieck, James P. G. Sterbenz:
08102 Working Group -- Requirements for Network Monitoring from an IDS Perspective. Network Attack Detection and Defense 2008 - [i1]Marc Dacier, Hervé Debar, Thorsten Holz, Engin Kirda, Jan Kohlrausch, Christopher Kruegel, Konrad Rieck, James P. G. Sterbenz:
8102 Working Group -- Attack Taxonomy. Network Attack Detection and Defense 2008 - 2007
- [j1]Konrad Rieck, Pavel Laskov:
Language models for detection of unknown attacks in network traffic. J. Comput. Virol. 2(4): 243-256 (2007) - [c6]Pavel Laskov, Konrad Rieck, Klaus-Robert Müller:
Machine Learning for Intrusion Detection. NATO ASI Mining Massive Data Sets for Security 2007: 366-373 - 2006
- [c5]Konrad Rieck, Pavel Laskov, Klaus-Robert Müller:
Efficient Algorithms for Similarity Measures over Sequential Data: A Look Beyond Kernels. DAGM-Symposium 2006: 374-383 - [c4]Konrad Rieck, Pavel Laskov:
Detecting Unknown Network Attacks Using Language Models. DIMVA 2006: 74-90 - [c3]Konrad Rieck, Pavel Laskov, Sören Sonnenburg:
Computation of Similarity Measures for Sequential Data using Generalized Suffix Trees. NIPS 2006: 1177-1184 - 2005
- [c2]Pavel Laskov, Patrick Düssel, Christin Schäfer, Konrad Rieck:
Learning Intrusion Detection: Supervised or Unsupervised?. ICIAP 2005: 50-57 - [c1]Pavel Laskov, Konrad Rieck, Christin Schäfer, Klaus-Robert Müller:
Visualization of anomaly detection using prediction sensitivity. Sicherheit 2005: 197-208
Coauthor Index
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Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-04-21 17:50 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
