Suchparameter:
  • Suche in Namens-Datensätzen nach: "wurzenberger" ("wurzenberger" als Name interpretiert)
  • Suche eingeschränkt auf Publikationsarten: Alle
  • Suche eingeschränkt auf Zeitraum: Alle Daten in der Datenbank
Mit Ihren Suchparametern wurden 29 passende Datensätze gefunden:
29 - Center "Digital Safety & Security"




Zeitschriftenartikel:


  1. Quelle: Center "Digital Safety & Security"

    M. Landauer, F. Skopik, M. Wurzenberger, A. Rauber:
    "System Log Clustering Approaches for Cyber Security Applications: A Survey";
    Computers & Security, - (2020), 92; S. 1 - 17.

  2. Quelle: Center "Digital Safety & Security"

    M. Landauer, M. Wurzenberger, F. Skopik, G. Settanni, P. Filzmoser:
    "Dynamic Log File Analysis: An Unsupervised Cluster Evolution Approach for Anomaly Detection";
    Computers & Security, 79 (2018), S. 94 - 116.

  3. Quelle: Center "Digital Safety & Security"

    G. Settanni, F. Skopik, M. Wurzenberger, R. Fiedler:
    "Countering Targeted Cyber Attacks in Industry 4.0 through Anomaly Detection for Self-Adapting CPS";
    Elektrotechnik & Informationstechnik, 135 (2018), 3; S. 278 - 285.

  4. Quelle: Center "Digital Safety & Security"

    F. Skopik, M. Wurzenberger, R. Fiedler:
    "synERGY: Detecting advanced attacks across multiple layers of cyber-physical systems";
    ERCIM News, 114 (2018), S. 30 - 31.

  5. Quelle: Center "Digital Safety & Security"

    M. Wurzenberger, F. Skopik:
    "The BAESE Testbed - Analytic Evaluation of IT Security Tools in Specified Network Environments";
    ERCIM News, 107 (2016), S. 51 - 52.

  6. Quelle: Center "Digital Safety & Security"

    M. Wurzenberger, F. Skopik:
    "The BÆSE Testbed - Analytic Evaluation of IT Security Tools in Specified Network Environments";
    ERCIM News, 107 (2016), S. 51 - 52.

  7. Quelle: Center "Digital Safety & Security"

    M. Wurzenberger, F. Skopik, G. Settanni, W. Scherrer:
    "Complex Log File Synthesis for Rapid Sandbox-Benchmarking of Security- and Computer Network Analysis Tools";
    Information Systems, 60 (2016), S. 13 - 33.


Buchbeiträge:


  1. Quelle: Center "Digital Safety & Security"

    I. Friedberg, M. Wurzenberger, A. Al Balushi, B. Kang:
    "From Monitoring, Logging, and Network Analysis to Threat Intelligence Extraction";
    in: "Collaborative Cyber Threat Intelligence", CRC Press, Abingdon, 2017, ISBN: 978-1138031821, S. 69 - 128.

  2. Quelle: Center "Digital Safety & Security"

    M. Wurzenberger, F. Skopik, G. Settanni:
    "Big Data for Cybersecurity";
    in: "Encyclopedia of Big Data Technologies", Springer, Cham, 2018, ISBN: 978-3-319-63962-8, S. 1 - 9.


Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):


  1. Quelle: Center "Digital Safety & Security"

    I. Friedberg, S. McLaughlin, P. Smith, M. Wurzenberger:
    "Towards a Resilience Metric Framework for Cyber-Physical Systems";
    Vortrag: 4th International Symposium for ICS & SCADA Cyber Security Research 2016, Belfast; 23.08.2016 - 25.08.2016; in: "4th International Symposium for ICS & SCADA Cyber Security Research 2016", BCS, (2016), ISSN: 1477-9358; S. 19 - 22.

  2. Quelle: Center "Digital Safety & Security"

    M. Landauer, F. Skopik, M. Wurzenberger, W. Hotwagner, A. Rauber:
    "A Framework for Cyber Threat Intelligence Extraction from Raw Log Data";
    Vortrag: International Conference on Big Data, Los Angeles; 09.12.2019 - 12.12.2019; in: "Proceedings of the 2019 IEEE International Conference on Big Data (Big Data)", IEEE, (2019), ISBN: 978-1-7281-0858-2; S. 3200 - 3209.

  3. Quelle: Center "Digital Safety & Security"

    M. Landauer, F. Skopik, M. Wurzenberger, W. Hotwagner, A. Rauber:
    "Visualizing Syscalls using Self-Organizing Maps for System Intrusion Detection";
    Poster: ICISSP, Valletta; 25.02.2020 - 27.02.2020; in: "Proceedings of the 6th International Conference on Information Systems Security and Privacy", SciTePress, 1 (2020), ISBN: 978-989-758-399-5; S. 349 - 360.

  4. Quelle: Center "Digital Safety & Security"

    M. Landauer, M. Wurzenberger, F. Skopik, G. Settanni, P. Filzmoser:
    "Time Series Analysis: Unsupervised Anomaly Detection Beyond Outlier Detection";
    Vortrag: 14th International Conference on Information Security Practice and Experience (ISPEC 2018), Tokyo; 25.09.2018 - 27.09.2018; in: "Information Security Practice and Experience", Springer, Cham, (2018), ISBN: 978-3-319-99806-0; S. 19 - 36.

  5. Quelle: Center "Digital Safety & Security"

    G. Settanni, Y. Shovgenya, F. Skopik, M. Wurzenberger, R. Graf, R. Fiedler:
    "Acquiring Cyber Threat Intelligence through Security Information Correlation";
    Vortrag: 3rd IEEE International Conference on Cybernetics (CYBCONF-2017) WS/SS, Exeter - United Kingdom; 21.06.2017 - 23.06.2017; in: "2017 3rd IEEE International Conference on Cybernetics (CYBCONF)", IEEE eXpress Conference Publishing, (2017), ISBN: 978-1-5386-2201-8; S. 415 - 421.

  6. Quelle: Center "Digital Safety & Security"

    G. Settanni, F. Skopik, A. Karaj, M. Wurzenberger, R. Fiedler:
    "Protecting Cyber Physical Production Systems using Anomaly Detection to enable Self-adaptation";
    Vortrag: 1st IEEE International Conference on Industrial Cyber-Physical Systems (ICPS 2018), Saint Petersburg; 15.05.2018 - 18.05.2018; in: "USB Proceedings 2018 IEEE Industrial Cyber-Physical Systems (ICPS)", IEEE, (2018), ISBN: 978-1-5386-6530-5; S. 173 - 180.

  7. Quelle: Center "Digital Safety & Security"

    G. Settanni, F. Skopik, M. Wurzenberger, R. Graf, R. Fiedler:
    "Correlating Cyber Incident Information to Establish Situational Awareness in Critical Infrastructures";
    Vortrag: Fourteenth annual conference on Privacy, Security and Trust, Auckland - New Zeland; 12.12.2016 - 14.12.2016; in: "Proceedings of the 14th International Conference on Privacy, Security and Trust", IEEE, http://ieeexplore.ieee.org/document/7906940/ (2016), ISBN: 978-1-5090-4379-8; S. 78 - 81.

  8. Quelle: Center "Digital Safety & Security"

    F. Skopik, M. Wurzenberger, G. Settanni, R. Fiedler:
    "Establishing Cyber Situational Awareness through Incident Information Clustering";
    Vortrag: International Conference on Cyber Situational Awareness Data Analytics and Assessment, London, UK; 08.06.2015 - 09.06.2015; in: "International Conference on Cyber Situational Awareness Data Analytics and Assessment", Cyril Onwubiko, London (2015), ISBN: 978-0-9932338-0-7; S. 300 - 314.

  9. Quelle: Center "Digital Safety & Security"

    M. Wurzenberger, M. Landauer, F. Skopik, W. Kastner:
    "AECID-PG: A Tree-Based Log Parser Generator To Enable Log Analysis";
    Vortrag: IFIP/IEEE IM 2019 Workshop: 4th IEEE/IFIP International Workshop on Analytics for Network and Service Management, Washington; 08.04.2019; in: "IFIP/IEEE IM 2019 Workshop: 4th IEEE/IFIP International Workshop on Analytics for Network and Service Management", (2019), ISBN: 978-3-903176-15-7; S. 7 - 12.

  10. Quelle: Center "Digital Safety & Security"

    M. Wurzenberger, F. Skopik, R. Fiedler, W. Kastner:
    "Applying High-Performance Bioinformatics Tools for Outlier Detection in Log Data";
    Vortrag: 3rd IEEE International Conference on Cybernetics (CYBCONF-2017) WS/SS, Exeter - United Kingdom; 21.06.2017 - 23.06.2017; in: "2017 3rd IEEE International Conference on Cybernetics (CYBCONF)", IEEE eXpress Conference Publishing, (2017), ISBN: 978-1-5386-2201-8; S. 399 - 406.

  11. Quelle: Center "Digital Safety & Security"

    M. Wurzenberger, F. Skopik, R. Fiedler, W. Kastner:
    "Discovering Insider Threats from Log Data with High-Performance Bioniformatics Tools";
    Vortrag: MIST' 16, Wien; 28.10.2016; in: "MIST' 16 Proceedings of the 2016 International Workshop on Managing Inisider Security Threats", ACM, New York (2016), ISBN: 9781450345712; S. 109 - 112.

  12. Quelle: Center "Digital Safety & Security"

    M. Wurzenberger, F. Skopik, M. Landauer, P. Greitbauer, R. Fiedler, W. Kastner:
    "Incremental Clustering for Semi-Supervised Anomaly Detection applied on Log Data";
    Vortrag: ARES - International Conference on Availability, Reliability and Security, Reggio Calabria; 29.08.2017 - 01.09.2017; in: "Proceedings of the 12th International Conference on Availability, Reliability and Security", The Association for Computing Machinery, New York, (2017), ISBN: 978-1-4503-5257-4; S. 1 - 6.

  13. Quelle: Center "Digital Safety & Security"

    M. Wurzenberger, F. Skopik, G. Settanni, R. Fiedler:
    "AECID: A Self-learning Anomaly Detection Approach Based on Light-weight Log Parser Models";
    Vortrag: 4th International Conference on Information Systems Security and Privacy(ICISSP 2018), Funchal, Portugal; 22.01.2018 - 24.01.2018; in: "Proceedings of the 4th International Conference on Information Systems Security and Privacy, 2018", SCITEPRESS digital library, 2018, (2018), ISBN: 978-989-758-282-0; S. 386 - 397.

  14. Quelle: Center "Digital Safety & Security"

    M. Wurzenberger, F. Skopik, G. Settanni, R. Fiedler:
    "Beyond Gut Instincts: Understanding, Rating and Comparing Self-Learning ICT Intrusion Detecion Systems";
    Poster: International Conference on Cyber Situational Awareness Data Analytics and Assessment, London, UK; 08.06.2015 - 09.06.2015; in: "International Conference on Cyber Situational Awareness Data Analytics and Assessment", Cyril Onwubiko, London (2015), ISBN: 978-0-9932338-0-7; S. 205 - 207.


Vorträge und Posterpräsentationen (ohne Tagungsband-Eintrag):


  1. Quelle: Center "Digital Safety & Security"

    F. Skopik, M. Wurzenberger, M. Landauer:
    "Machine Learning für Logdatenanalyse - Ein Ausblick auf Morgen";
    Vortrag: IKT Sicherheitskonferenz 2019, Fürstenfeld (eingeladen); 01.10.2019 - 02.10.2019.

  2. Quelle: Center "Digital Safety & Security"

    M. Wurzenberger:
    "How Can AI Improve Cyber Situational Awareness?";
    Vortrag: European Big Data Value Forum, Wien (eingeladen); 12.11.2018 - 14.11.2018.

  3. Quelle: Center "Digital Safety & Security"

    M. Wurzenberger, M. Landauer:
    "Applying Machine Learning for System Log Data Analysis";
    Vortrag: European Security and Defence College (ESDC), Infrastructures in the Context of Digitization Course - ICD (2019-2020/254/1), Wien (eingeladen); 16.10.2019 - 18.10.2019.

  4. Quelle: Center "Digital Safety & Security"

    M. Wurzenberger, M. Landauer:
    "ÆCID: A Self-Learning Anomaly Detection Approach Based on Light-weight Log Analytics";
    Vortrag: BSides Vienna 2019, Wien; 30.11.2019.


Diplom- und Master-Arbeiten (eigene und betreute):


  1. Quelle: Center "Digital Safety & Security"

    M. Landauer:
    "Dynamic Log File Analysis: An Unsupervised Cluster Evolution Approach for Anomaly Detection";
    Betreuer/in(nen): P. Filzmoser, F. Skopik, M. Wurzenberger; TU Wien, Fakultät für Informatik, 2018; Abschlussprüfung: 11.04.2018.

  2. Quelle: Center "Digital Safety & Security"

    M. Wurzenberger:
    "Synthetic Log Data Modeling for the Evaluation of Intrusion Detection Systems";
    Betreuer/in(nen): W. Scherrer, F. Skopik; TU Wien, 2015; Abschlussprüfung: 24.11.2015.