3 Search Results for "Rieck, Konrad"

Document
DOI: 10.4230/DagRep.12.7.41
Security of Machine Learning (Dagstuhl Seminar 22281)

Authors: Battista Biggio, Nicholas Carlini, Pavel Laskov, Konrad Rieck, and Antonio Emanuele Cinà

Published in: Dagstuhl Reports, Volume 12, Issue 7 (2023)

Abstract
Machine learning techniques, especially deep neural networks inspired by mathematical models of human intelligence, have reached an unprecedented success on a variety of data analysis tasks. The reliance of critical modern technologies on machine learning, however, raises concerns on their security, especially since powerful attacks against mainstream learning algorithms have been demonstrated since the early 2010s. Despite a substantial body of related research, no comprehensive theory and design methodology is currently known for the security of machine learning. The proposed seminar aims at identifying potential research directions that could lead to building the scientific foundation for the security of machine learning. By bringing together researchers from machine learning and information security communities, the seminar is expected to generate new ideas for security assessment and design in the field of machine learning.
Cite as

Battista Biggio, Nicholas Carlini, Pavel Laskov, Konrad Rieck, and Antonio Emanuele Cinà. Security of Machine Learning (Dagstuhl Seminar 22281). In Dagstuhl Reports, Volume 12, Issue 7, pp. 41-61, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{biggio_et_al:DagRep.12.7.41,
  author =	{Biggio, Battista and Carlini, Nicholas and Laskov, Pavel and Rieck, Konrad and Cin\`{a}, Antonio Emanuele},
  title =	{{Security of Machine Learning (Dagstuhl Seminar 22281)}},
  pages =	{41--61},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2023},
  volume =	{12},
  number =	{7},
  editor =	{Biggio, Battista and Carlini, Nicholas and Laskov, Pavel and Rieck, Konrad and Cin\`{a}, Antonio Emanuele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.12.7.41},
  URN =		{urn:nbn:de:0030-drops-176117},
  doi =		{10.4230/DagRep.12.7.41},
  annote =	{Keywords: adversarial machine learning, machine learning security}
}
Document
DOI: 10.4230/DagSemProc.08102.4
4. 8102 Working Group – Attack Taxonomy

Authors: Marc Daciér, Hervé Debar, Thorsten Holz, Engin Kirda, Jan Kohlrausch, Christopher Kruegel, Konrad Rieck, and James Sterbenz

Published in: Dagstuhl Seminar Proceedings, Volume 8102, Perspectives Workshop: Network Attack Detection and Defense (2008)

Abstract
The starting point of this working group was the question about the kinds of attacks that can be detected by inspecting in network traffic. In general, we identified four major problems that network-based intrusion detection systems are facing: 1. Encrypted network traffic 2. Application-level attacks 3. Performance 4. Evasion attack.
Cite as

Marc Daciér, Hervé Debar, Thorsten Holz, Engin Kirda, Jan Kohlrausch, Christopher Kruegel, Konrad Rieck, and James Sterbenz. 4. 8102 Working Group – Attack Taxonomy. In Perspectives Workshop: Network Attack Detection and Defense. Dagstuhl Seminar Proceedings, Volume 8102, pp. 1-4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{dacier_et_al:DagSemProc.08102.4,
  author =	{Daci\'{e}r, Marc and Debar, Herv\'{e} and Holz, Thorsten and Kirda, Engin and Kohlrausch, Jan and Kruegel, Christopher and Rieck, Konrad and Sterbenz, James},
  title =	{{4. 8102 Working Group – Attack Taxonomy}},
  booktitle =	{Perspectives Workshop: Network Attack Detection and Defense},
  pages =	{1--4},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8102},
  editor =	{Georg Carle and Falko Dressler and Richard A. Kemmerer and Hartmut K\"{o}nig and Christopher Kruegel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.08102.4},
  URN =		{urn:nbn:de:0030-drops-14955},
  doi =		{10.4230/DagSemProc.08102.4},
  annote =	{Keywords: Intrusion detection and prevention, attack response and countermeasures, reactive security, automated security, survivability and self-protection, ma network monitoring, flow analysis, denial of service detection and response, event correlation}
}
Document
DOI: 10.4230/DagSemProc.08102.6
6. 08102 Working Group – Requirements for Network Monitoring from an IDS Perspective

Authors: Lothar Braun, Falko Dressler, Thorsten Holz, Engin Kirda, Jan Kohlrausch, Christopher Kruegel, Tobias Limmer, Konrad Rieck, and James Sterbenz

Published in: Dagstuhl Seminar Proceedings, Volume 8102, Perspectives Workshop: Network Attack Detection and Defense (2008)

Abstract
Detection of malicious traffic is based on its input data, the information that is co-ming from network-based monitoring systems. Best detection rates would only be possible by monitoring all data transferred over all network lines in a distributed net-work. Monitoring and reporting this amount of data are feasible in neither today's, nor will be in future's systems. Later analysis like stateful inspection of the traffic imposes even more processing costs. But only at this level of monitoring and analysis there may be a chance to capture all attacks inside a system. So there needs to be a trade-off between detection success and the processing costs.
Cite as

Lothar Braun, Falko Dressler, Thorsten Holz, Engin Kirda, Jan Kohlrausch, Christopher Kruegel, Tobias Limmer, Konrad Rieck, and James Sterbenz. 6. 08102 Working Group – Requirements for Network Monitoring from an IDS Perspective. In Perspectives Workshop: Network Attack Detection and Defense. Dagstuhl Seminar Proceedings, Volume 8102, pp. 1-4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{braun_et_al:DagSemProc.08102.6,
  author =	{Braun, Lothar and Dressler, Falko and Holz, Thorsten and Kirda, Engin and Kohlrausch, Jan and Kruegel, Christopher and Limmer, Tobias and Rieck, Konrad and Sterbenz, James},
  title =	{{6. 08102 Working Group – Requirements for Network Monitoring from an IDS Perspective}},
  booktitle =	{Perspectives Workshop: Network Attack Detection and Defense},
  pages =	{1--4},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8102},
  editor =	{Georg Carle and Falko Dressler and Richard A. Kemmerer and Hartmut K\"{o}nig and Christopher Kruegel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.08102.6},
  URN =		{urn:nbn:de:0030-drops-14970},
  doi =		{10.4230/DagSemProc.08102.6},
  annote =	{Keywords: Intrusion detection and prevention, attack response and countermeasures, reactive security, automated security, survivability and self-protection, ma network monitoring, flow analysis, denial of service detection and response, event correlation}
}
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