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Pavel Laskov
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2020 – today
- 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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