The Missing Link in Network Intrusion Detection: Taking AI/ML Research Efforts to Users-Reference-Cited by-同舟云学术

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The Missing Link in Network Intrusion Detection: Taking AI/ML Research Efforts to Users

Published:2024 Issue: Volume:12 Page:79815-79837
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Dietz Katharina¹^ORCID,Mühlhauser Michael²^ORCID,Kögel Jochen³^ORCID,Schwinger Stephan⁴^ORCID,Sichermann Marleen¹^ORCID,Seufert Michael⁵^ORCID,Herrmann Dominik²^ORCID,Hoßfeld Tobias¹^ORCID

Affiliation:

1. Chair of Communication Networks, University of Würzburg, Würzburg, Germany

2. Privacy and Security in Information Systems Group, University of Bamberg, Bamberg, Germany

3. IsarNet Software Solutions GmbH, Munich, Germany

4. genua GmbH, Kirchheim, Germany

5. Chair of Networked Embedded Systems and Communication Systems, University of Augsburg, Augsburg, Germany

Funder

German Federal Ministry of Education and Research

WINTERMUTE

BMBF

Deutsche Forschungsgemeinschaft

Bavarian Ministry of Economics, Regional Development and Energy

VIPNANO

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10540566.pdf?arnumber=10540566

Reference221 articles.

1. Everybody’s Got ML, Tell Me What Else You Have: Practitioners’ Perception of ML-Based Security Tools and Explanations

2. Security Operations Center: A Systematic Study and Open Challenges

3. A comprehensive survey on machine learning for networking: evolution, applications and research opportunities

4. A survey of techniques for internet traffic classification using machine learning

5. A Survey on Information Visualization for Network and Service Management

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