Florian Skopik

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Markus WurzenbergerAIT Austrian Institute of TechnologyVerified email at ait.ac.at
Max LandauerAIT Austrian Institute of TechnologyVerified email at ait.ac.at
Schahram DustdarProfessor of Computer Science, Member of Academia Europaea, IEEE|EAI|AAIA Fellow, TU Wien, AustriaVerified email at dsg.tuwien.ac.at
Daniel SchallSiemens TechnologyVerified email at siemens.com
Giuseppe SettanniAustrian Institute of TechnologyVerified email at ait.ac.at
Paul SmithAIT Austrian Institute of TechnologyVerified email at ait.ac.at
Maria LeitnerUniversity of RegensburgVerified email at ur.de
Andreas RauberTU Wien / Vienna University of TechnologyVerified email at ifs.tuwien.ac.at
Zhendong MaLuxoft / DXC TechnologyVerified email at dxc.com
Ivo FriedbergQueen's University BelfastVerified email at qub.ac.uk
Wolfgang KastnerAutomation Systems Group, TU WienVerified email at auto.tuwien.ac.at
Hong-Linh TruongAalto UniversityVerified email at aalto.fi
Gregor LangnerAIT Austrian Institute of TechnologyVerified email at ait.ac.at
Peter FilzmoserProfessor of Statistics, TU WienVerified email at tuwien.ac.at
Christoph Mayr-DornInstitute for Software Systems Engineering, Johannes Kepler University, LinzVerified email at jku.at
Konstantin BöttingerFraunhofer AISECVerified email at aisec.fraunhofer.de
F KupzogSenior Scientist, AIT Austrian Institute of TechnologyVerified email at kupzog.de
Gerd Stefan BrostFraunhofer AISECVerified email at aisec.fraunhofer.de
Stefan RassFull Professor, LIT Secure and Correct Systems Lab, Johannes Kepler University Linz, AustriaVerified email at jku.at
Wolfgang ScherrerAo.Univ. Professor, Technische Universität WienVerified email at tuwien.ac.at

Florian Skopik

AIT Austrian Institute of Technology

Verified email at ait.ac.at - Homepage

Computer Security Cyber Threat Intelligence Anomaly Detection Machine Learning


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A problem shared is a problem halved: A survey on the dimensions of collective cyber defense through security information sharing F Skopik, G Settanni, R Fiedler Computers & Security 60, 154-176, 2016	291	2016
Combating advanced persistent threats: From network event correlation to incident detection I Friedberg, F Skopik, G Settanni, R Fiedler Computers & Security 48, 35-57, 2015	261	2015
Modeling and mining of dynamic trust in complex service-oriented systems F Skopik, D Schall, S Dustdar Socially Enhanced Services Computing: Modern Models and Algorithms for …, 2011	165	2011
System log clustering approaches for cyber security applications: A survey M Landauer, F Skopik, M Wurzenberger, A Rauber Computers & Security 92, 101739, 2020	98	2020
Dynamic log file analysis: An unsupervised cluster evolution approach for anomaly detection M Landauer, M Wurzenberger, F Skopik, G Settanni, P Filzmoser computers & security 79, 94-116, 2018	79	2018
Start trusting strangers? bootstrapping and prediction of trust F Skopik, D Schall, S Dustdar International conference on web information systems engineering, 275-289, 2009	73	2009
A collaborative cyber incident management system for European interconnected critical infrastructures G Settanni, F Skopik, Y Shovgenya, R Fiedler, M Carolan, D Conroy, ... Journal of Information Security and Applications 34, 166-182, 2017	69	2017
Dealing with advanced persistent threats in smart grid ICT networks F Skopik, I Friedberg, R Fiedler ISGT 2014, 1-5, 2014	62	2014
A survey on threats and vulnerabilities in smart metering infrastructures F Skopik, Z Ma, T Bleier, H Grüneis International Journal of Smart Grid and Clean Energy 1 (1), 22-28, 2012	60	2012
Expert discovery and interactions in mixed service-oriented systems D Schall, F Skopik, S Dustdar IEEE Transactions on services computing 5 (2), 233-245, 2011	60	2011
Under false flag: using technical artifacts for cyber attack attribution F Skopik, T Pahi Cybersecurity 3, 1-20, 2020	59	2020
Trust and reputation mining in professional virtual communities F Skopik, HL Truong, S Dustdar International Conference on Web Engineering, 76-90, 2009	58	2009
Interaction mining and skill-dependent recommendations for multi-objective team composition C Dorn, F Skopik, D Schall, S Dustdar Data & Knowledge Engineering 70 (10), 866-891, 2011	56	2011
Smart grid security: Innovative solutions for a modernized grid F Skopik, PD Smith Syngress, 2015	53	2015
Runtime behavior monitoring and self-adaptation in service-oriented systems H Psaier, L Juszczyk, F Skopik, D Schall, S Dustdar 2010 Fourth IEEE International Conference on Self-Adaptive and Self …, 2010	53	2010
Semi-synthetic data set generation for security software evaluation F Skopik, G Settanni, R Fiedler, I Friedberg 2014 Twelfth Annual International Conference on Privacy, Security and Trust …, 2014	51	2014
Incremental clustering for semi-supervised anomaly detection applied on log data M Wurzenberger, F Skopik, M Landauer, P Greitbauer, R Fiedler, ... Proceedings of the 12th International Conference on Availability …, 2017	50	2017
Deep learning for anomaly detection in log data: A survey M Landauer, S Onder, F Skopik, M Wurzenberger Machine Learning with Applications 12, 100470, 2023	43	2023
Protecting cyber physical production systems using anomaly detection to enable self-adaptation G Settanni, F Skopik, A Karaj, M Wurzenberger, R Fiedler 2018 IEEE Industrial Cyber-Physical Systems (ICPS), 173-180, 2018	42	2018
Attack vectors to metering data in smart grids under security constraints F Skopik, Z Ma 2012 IEEE 36th Annual Computer Software and Applications Conference …, 2012	40	2012

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