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2020 – today
- 2024
[i12]Hervé Debar, Sven Dietrich
, Pavel Laskov, Emil C. Lupu, Eirini Ntoutsi:
Emerging Security Challenges of Large Language Models. CoRR abs/2412.17614 (2024)- [i11]Saskia Laura Schröer, Giovanni Apruzzese, Soheil Human, Pavel Laskov, Hyrum S. Anderson, Edward W. N. Bernroider, Aurore Fass, Ben Nassi, Vera Rimmer, Fabio Roli, Samer Salam, Ashley Shen, Ali Sunyaev, Tim Wadwha-Brown, Isabel Wagner, Gang Wang:
SoK: On the Offensive Potential of AI. CoRR abs/2412.18442 (2024) - 2023
- [j20]Giovanni Apruzzese, Pavel Laskov, Edgardo Montes de Oca, Wissam Mallouli, Luis Burdalo Rapa, Athanasios Vasileios Grammatopoulos, Fabio Di Franco:
The Role of Machine Learning in Cybersecurity. DTRAP 4(1): 8:1-8:38 (2023) - [c38]Giovanni Apruzzese, Pavel Laskov, Johannes Schneider:
SoK: Pragmatic Assessment of Machine Learning for Network Intrusion Detection. EuroS&P 2023: 592-614 - [i10]Giovanni Apruzzese, Pavel Laskov, Johannes Schneider:
SoK: Pragmatic Assessment of Machine Learning for Network Intrusion Detection. CoRR abs/2305.00550 (2023) - [i9]Sven Dietrich, Frank Kargl, Hartmut König, Pavel Laskov, Artur Hermann:
Network Attack Detection and Defense - AI-Powered Threats and Responses (Dagstuhl Seminar 23431). Dagstuhl Reports 13(10): 90-129 (2023) - 2022
- [j19]Giovanni Apruzzese, Rodion Vladimirov, Aliya Tastemirova, Pavel Laskov:
Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples. IEEE Trans. Netw. Serv. Manag. 19(4): 5312-5332 (2022) - [c37]Giovanni Apruzzese, Pavel Laskov, Aliya Tastemirova:
SoK: The Impact of Unlabelled Data in Cyberthreat Detection. EuroS&P 2022: 20-42 - [c36]François Goupil, Pavel Laskov, Irdin Pekaric, Michael Felderer, Alexander Dürr, Frédéric Thiesse:
Towards Understanding the Skill Gap in Cybersecurity. ITiCSE (1) 2022: 477-483 - [i8]François Goupil, Pavel Laskov, Irdin Pekaric, Michael Felderer, Alexander Dürr, Frédéric Thiesse:
Towards Understanding the Skill Gap in Cybersecurity. CoRR abs/2204.13793 (2022) - [i7]Giovanni Apruzzese, Pavel Laskov, Aliya Tastemirova:
SoK: The Impact of Unlabelled Data in Cyberthreat Detection. CoRR abs/2205.08944 (2022) - [i6]Giovanni Apruzzese, Pavel Laskov, Edgardo Montes de Oca, Wissam Mallouli, Luis Burdalo Rapa, Athanasios Vasileios Grammatopoulos, Fabio Di Franco:
The Role of Machine Learning in Cybersecurity. CoRR abs/2206.09707 (2022) - [i5]Giovanni Apruzzese, Rodion Vladimirov, Aliya Tastemirova, Pavel Laskov:
Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples. CoRR abs/2207.01531 (2022) - [i4]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]Michele Russo, Nedim Srndic, Pavel Laskov:
Detection of illicit cryptomining using network metadata. EURASIP J. Inf. Secur. 2021(1): 11 (2021)
2010 – 2019
- 2017
- [i3]Battista Biggio, Igino Corona, Davide Maiorca, Blaine Nelson, Nedim Srndic, Pavel Laskov, Giorgio Giacinto, Fabio Roli:
Evasion Attacks against Machine Learning at Test Time. CoRR abs/1708.06131 (2017) - 2016
- [j17]Nedim Srndic, Pavel Laskov:
Hidost: a static machine-learning-based detector of malicious files. EURASIP J. Inf. Secur. 2016: 22 (2016) - 2014
- [c35]Nedim Srndic, Pavel Laskov:
Practical Evasion of a Learning-Based Classifier: A Case Study. IEEE Symposium on Security and Privacy 2014: 197-211 - 2013
- [j16]Anthony D. Joseph, Pavel Laskov, Fabio Roli, J. Doug Tygar, Blaine Nelson:
Machine Learning Methods for Computer Security (Dagstuhl Perspectives Workshop 12371). Dagstuhl Manifestos 3(1): 1-30 (2013) - [c34]Nedim Srndic, Pavel Laskov:
Detection of Malicious PDF Files Based on Hierarchical Document Structure. NDSS 2013 - [c33]Battista Biggio, Igino Corona, Davide Maiorca, Blaine Nelson, Nedim Srndic, Pavel Laskov, Giorgio Giacinto, Fabio Roli:
Evasion Attacks against Machine Learning at Test Time. ECML/PKDD (3) 2013: 387-402 - 2012
- [j15]Cristian Grozea, Pavel Laskov:
Anomaly Detection at "supersonic" Speed. it Inf. Technol. 54(2): 82-89 (2012) - [j14]Marius Kloft, Pavel Laskov:
Security analysis of online centroid anomaly detection. J. Mach. Learn. Res. 13: 3681-3724 (2012) - [c32]Battista Biggio, Blaine Nelson, Pavel Laskov:
Poisoning Attacks against Support Vector Machines. ICML 2012 - [i2]Anthony D. Joseph, Pavel Laskov, Fabio Roli, J. Doug Tygar, Blaine Nelson:
Machine Learning Methods for Computer Security (Dagstuhl Perspectives Workshop 12371). Dagstuhl Reports 2(9): 109-130 (2012) - 2011
- [c31]Pavel Laskov, Nedim Srndic:
Static detection of malicious JavaScript-bearing PDF documents. ACSAC 2011: 373-382 - [c30]Blaine Nelson, Battista Biggio, Pavel Laskov:
Understanding the risk factors of learning in adversarial environments. AISec 2011: 87-92 - [c29]Blaine Nelson, Battista Biggio, Pavel Laskov:
Microbagging Estimators: An Ensemble Approach to Distance-weighted Classifiers. ACML 2011: 63-79 - [c28]Battista Biggio, Blaine Nelson, Pavel Laskov:
Support Vector Machines Under Adversarial Label Noise. ACML 2011: 97-112 - 2010
- [j13]Carsten Henneges, Pavel Laskov, Endang Darmawan, Juergen Backhaus, Bernd Kammerer, Andreas Zell:
A factorization method for the classification of infrared spectra. BMC Bioinform. 11: 561 (2010) - [j12]Pavel Laskov, Richard Lippmann:
Machine learning in adversarial environments. Mach. Learn. 81(2): 115-119 (2010) - [c27]Cristian Grozea, Zorana Bankovic, Pavel Laskov:
FPGA vs. Multi-core CPUs vs. GPUs: Hands-On Experience with a Sorting Application. Facing the Multicore-Challenge 2010: 105-117 - [c26]Tammo Krueger, Christian Gehl, Konrad Rieck, Pavel Laskov:
TokDoc: a self-healing web application firewall. SAC 2010: 1846-1853 - [c25]Konrad Rieck, Guido Schwenk, Tobias Limmer, Thorsten Holz, Pavel Laskov:
Botzilla: detecting the "phoning home" of malicious software. SAC 2010: 1978-1984 - [c24]Marius Kloft, Pavel Laskov:
Online Anomaly Detection under Adversarial Impact. AISTATS 2010: 405-412
2000 – 2009
- 2009
- [j11]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) - [j10]Georg Carle, Falko Dressler, Richard A. Kemmerer, Hartmut König, Christopher Kruegel, Pavel Laskov:
Network attack detection and defense - Manifesto of the Dagstuhl Perspective Workshop, March 2nd-6th, 2008. Comput. Sci. Res. Dev. 23(1): 15-25 (2009) - [c23]Pavel Laskov, Marius Kloft:
A framework for quantitative security analysis of machine learning. AISec 2009: 1-4 - [c22]Patrick Düssel, Christian Gehl, Pavel Laskov, Jens-Uwe Bußer, Christof Störmann, Jan Kästner:
Cyber-Critical Infrastructure Protection Using Real-Time Payload-Based Anomaly Detection. CRITIS 2009: 85-97 - [c21]Ulrich Greveler, Pavel Laskov, Sebastian Pape:
Sicherer Umgang mit sensiblen Daten - technische Prävention und Reaktionen auf Datenschutzverletzungen. GI Jahrestagung 2009: 186-190 - [c20]Dirk Haage, Ralph Holz, Heiko Niedermayer, Pavel Laskov:
CLIO - A Cross-Layer Information Service for Overlay Network Optimization. KiVS 2009: 279-284 - [c19]Marius Kloft, Ulf Brefeld, Sören Sonnenburg, Pavel Laskov, Klaus-Robert Müller, Alexander Zien:
Efficient and Accurate Lp-Norm Multiple Kernel Learning. NIPS 2009: 997-1005 - 2008
- [j9]Konrad Rieck, Pavel Laskov:
Linear-Time Computation of Similarity Measures for Sequential Data. J. Mach. Learn. Res. 9: 23-48 (2008) - [c18]Marius Kloft, Ulf Brefeld, Patrick Düssel, Christian Gehl, Pavel Laskov:
Automatic feature selection for anomaly detection. AISec 2008: 71-76 - [c17]Konrad Rieck, Thorsten Holz, Carsten Willems, Patrick Düssel, Pavel Laskov:
Learning and Classification of Malware Behavior. DIMVA 2008: 108-125 - [c16]Patrick Düssel, Christian Gehl, Pavel Laskov, Konrad Rieck:
Incorporation of Application Layer Protocol Syntax into Anomaly Detection. ICISS 2008: 188-202 - [c15]Vojtech Franc, Pavel Laskov, Klaus-Robert Müller:
Stopping conditions for exact computation of leave-one-out error in support vector machines. ICML 2008: 328-335 - [c14]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 - [i1]Georg Carle, Falko Dressler, Richard A. Kemmerer, Hartmut König, Christopher Kruegel, Pavel Laskov:
08102 Manifesto -- Perspectives Workshop: Network Attack Detection and Defense. Network Attack Detection and Defense 2008 - 2007
- [j8]Eric Filiol, Roland Büschkes, Pavel Laskov:
Foreword. J. Comput. Virol. 2(4): 241-242 (2007) - [j7]Konrad Rieck, Pavel Laskov:
Language models for detection of unknown attacks in network traffic. J. Comput. Virol. 2(4): 243-256 (2007) - [c13]Pavel Laskov, Konrad Rieck, Klaus-Robert Müller:
Machine Learning for Intrusion Detection. NATO ASI Mining Massive Data Sets for Security 2007: 366-373 - 2006
- [j6]Pavel Laskov, Christian Gehl, Stefan Krüger, Klaus-Robert Müller:
Incremental Support Vector Learning: Analysis, Implementation and Applications. J. Mach. Learn. Res. 7: 1909-1936 (2006) - [c12]Konrad Rieck, Pavel Laskov, Klaus-Robert Müller:
Efficient Algorithms for Similarity Measures over Sequential Data: A Look Beyond Kernels. DAGM-Symposium 2006: 374-383 - [c11]Konrad Rieck, Pavel Laskov:
Detecting Unknown Network Attacks Using Language Models. DIMVA 2006: 74-90 - [c10]Konrad Rieck, Pavel Laskov, Sören Sonnenburg:
Computation of Similarity Measures for Sequential Data using Generalized Suffix Trees. NIPS 2006: 1177-1184 - [e1]Roland Büschkes, Pavel Laskov:
Detection of Intrusions and Malware & Vulnerability Assessment, Third International Conference, DIMVA 2006, Berlin, Germany, July 13-14, 2006, Proceedings. Lecture Notes in Computer Science 4064, Springer 2006, ISBN 3-540-36014-X [contents] - 2005
- [c9]Pavel Laskov, Patrick Düssel, Christin Schäfer, Konrad Rieck:
Learning Intrusion Detection: Supervised or Unsupervised?. ICIAP 2005: 50-57 - [c8]Pavel Laskov, Konrad Rieck, Christin Schäfer, Klaus-Robert Müller:
Visualization of anomaly detection using prediction sensitivity. Sicherheit 2005: 197-208 - 2004
- [j5]Andreas Ziehe, Pavel Laskov, Guido Nolte, Klaus-Robert Müller:
A Fast Algorithm for Joint Diagonalization with Non-orthogonal Transformations and its Application to Blind Source Separation. J. Mach. Learn. Res. 5: 777-800 (2004) - [j4]Pavel Laskov, Christin Schäfer, Igor V. Kotenko, Klaus-Robert Müller:
Intrusion Detection in Unlabeled Data with Quarter-sphere Support Vector Machines. Prax. Inf.verarb. Kommun. 27(4): 228-236 (2004) - [c7]Pavel Laskov, Christin Schäfer, Igor V. Kotenko:
Intrusion detection in unlabeled data with quarter-sphere Support Vector Machines. DIMVA 2004: 71-82 - [c6]Caspar von Wrede, Pavel Laskov:
Using classification to determine the number of finger strokes on a multi-touch tactile device. ESANN 2004: 549-554 - 2003
- [j3]Chandra Kambhamettu, Dmitry B. Goldgof, Matthew He, Pavel Laskov:
3D nonrigid motion analysis under small deformations. Image Vis. Comput. 21(3): 229-245 (2003) - [j2]Pavel Laskov, Chandra Kambhamettu:
Curvature-Based Algorithms for Nonrigid Motion and Correspondence Estimation. IEEE Trans. Pattern Anal. Mach. Intell. 25(10): 1349-1354 (2003) - [c5]David M. J. Tax, Pavel Laskov:
Online SVM learning: from classification to data description and back. NNSP 2003: 499-508 - 2002
- [j1]Pavel Laskov:
Feasible Direction Decomposition Algorithms for Training Support Vector Machines. Mach. Learn. 46(1-3): 315-349 (2002) - 2001
- [c4]Pavel Laskov, Chandra Kambhamettu:
Comparison of 3D Algorithms for Non-rigid Motion and Correspondence Estimation. BMVC 2001: 1-10
1990 – 1999
- 1999
- [c3]Roman Erenshteyn, Pavel Laskov, David M. Saxe, Richard A. Foulds:
Distributed Output Encoding for Multi-Class Pattern Recognition. ICIAP 1999: 229-234 - [c2]Pavel Laskov:
An Improved Decomposition Algorithm for Regression Support Vector Machines. NIPS 1999: 484-490 - 1996
- [c1]Roman Erenshteyn, Pavel Laskov, Richard A. Foulds, Lynn Messing, Garland Stern:
Recognition approach to gesture language understanding. ICPR 1996: 431-435
Coauthor Index
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