Zobraziť v EDS

Optical Network Security Management: Requirements, Architecture and Efficient Machine Learning Models for Detection of Evolving Threats [Invited]

Uložené v:
Podrobná bibliografia
Názov: Optical Network Security Management: Requirements, Architecture and Efficient Machine Learning Models for Detection of Evolving Threats [Invited]
Autori: Furdek Prekratic, Marija, 1985, Natalino Da Silva, Carlos, 1987, Giglio, Andrea Di, Schiano, Marco
Zdroj: Skydda optiska kommunikationsnätverk från cyber-säkerhetsattacker Journal of Optical Communications and Networking. 13(2):A144-A155
Predmety: Efficiency, Economic and social effects, Learning systems, Dimensionality reduction, Fiber optic networks, Network architecture, Semi-supervised learning, Infrastructure as a service (IaaS), Optical communication
Popis: As the communication infrastructure that sustains critical societal services, optical networks need to function in a secure and agile way. Thus, cognitive and automated security management functionalities are needed, fueled by the proliferating machine learning (ML) techniques and compatible with common network control entities and procedures. Automated management of optical network security requires advancements both in terms of performance and efficiency of ML approaches for security diagnostics, as well as novel management architectures and functionalities. This paper tackles these challenges by proposing a novel functional block called Security Operation Center (SOC), describing its architecture, specifying key requirements on the supported functionalities and providing guidelines on its integration with optical layer controller. Moreover, to boost efficiency of ML-based security diagnostic techniques when processing high-dimensional optical performance monitoring data in the presence of previously unseen physical-layer attacks, we combine unsupervised and semi-supervised learning techniques with three different dimensionality reduction methods and analyze the resulting performance and trade-offs between ML accuracy and run time complexity.
Popis súboru: electronic
Prístupová URL adresa: https://research.chalmers.se/publication/523192
https://research.chalmers.se/publication/519924
https://research.chalmers.se/publication/522115
https://research.chalmers.se/publication/523192/file/523192_Fulltext.pdf
Databáza: SwePub
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://research.chalmers.se/publication/523192#
    Name: EDS - SwePub (s4221598)
    Category: fullText
    Text: View record in SwePub
  – Url: https://resolver.ebscohost.com/openurl?sid=EBSCO:edsswe&genre=article&issn=19430620&ISBN=&volume=13&issue=2&date=20210101&spage=A144&pages=&title=Skydda optiska kommunikationsnätverk från cyber-säkerhetsattacker Journal of Optical Communications and Networking&atitle=Optical%20Network%20Security%20Management%3A%20Requirements%2C%20Architecture%20and%20Efficient%20Machine%20Learning%20Models%20for%20Detection%20of%20Evolving%20Threats%20%5BInvited%5D&aulast=Furdek%20Prekratic%2C%20Marija&id=DOI:10.1364/JOCN.402884
    Name: Full Text Finder
    Category: fullText
    Text: Full Text Finder
    Icon: https://imageserver.ebscohost.com/branding/images/FTF.gif
    MouseOverText: Full Text Finder
  – Url: https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=EBSCO&SrcAuth=EBSCO&DestApp=WOS&ServiceName=TransferToWoS&DestLinkType=GeneralSearchSummary&Func=Links&author=Prekratic%20F
    Name: ISI
    Category: fullText
    Text: Nájsť tento článok vo Web of Science
    Icon: https://imagesrvr.epnet.com/ls/20docs.gif
    MouseOverText: Nájsť tento článok vo Web of Science
Header DbId: edsswe
DbLabel: SwePub
An: edsswe.oai.research.chalmers.se.3dfdf500.3c39.4580.b662.9fd37d486eb3
RelevancyScore: 1004
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 1004.00384521484
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Optical Network Security Management: Requirements, Architecture and Efficient Machine Learning Models for Detection of Evolving Threats [Invited]
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Furdek+Prekratic%2C+Marija%22">Furdek Prekratic, Marija</searchLink>, 1985<br /><searchLink fieldCode="AR" term="%22Natalino+Da+Silva%2C+Carlos%22">Natalino Da Silva, Carlos</searchLink>, 1987<br /><searchLink fieldCode="AR" term="%22Giglio%2C+Andrea+Di%22">Giglio, Andrea Di</searchLink><br /><searchLink fieldCode="AR" term="%22Schiano%2C+Marco%22">Schiano, Marco</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <i>Skydda optiska kommunikationsnätverk från cyber-säkerhetsattacker Journal of Optical Communications and Networking</i>. 13(2):A144-A155
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Efficiency%22">Efficiency</searchLink><br /><searchLink fieldCode="DE" term="%22Economic+and+social+effects%22">Economic and social effects</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+systems%22">Learning systems</searchLink><br /><searchLink fieldCode="DE" term="%22Dimensionality+reduction%22">Dimensionality reduction</searchLink><br /><searchLink fieldCode="DE" term="%22Fiber+optic+networks%22">Fiber optic networks</searchLink><br /><searchLink fieldCode="DE" term="%22Network+architecture%22">Network architecture</searchLink><br /><searchLink fieldCode="DE" term="%22Semi-supervised+learning%22">Semi-supervised learning</searchLink><br /><searchLink fieldCode="DE" term="%22Infrastructure+as+a+service+%28IaaS%29%22">Infrastructure as a service (IaaS)</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+communication%22">Optical communication</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: As the communication infrastructure that sustains critical societal services, optical networks need to function in a secure and agile way. Thus, cognitive and automated security management functionalities are needed, fueled by the proliferating machine learning (ML) techniques and compatible with common network control entities and procedures. Automated management of optical network security requires advancements both in terms of performance and efficiency of ML approaches for security diagnostics, as well as novel management architectures and functionalities. This paper tackles these challenges by proposing a novel functional block called Security Operation Center (SOC), describing its architecture, specifying key requirements on the supported functionalities and providing guidelines on its integration with optical layer controller. Moreover, to boost efficiency of ML-based security diagnostic techniques when processing high-dimensional optical performance monitoring data in the presence of previously unseen physical-layer attacks, we combine unsupervised and semi-supervised learning techniques with three different dimensionality reduction methods and analyze the resulting performance and trade-offs between ML accuracy and run time complexity.
– Name: Format
  Label: File Description
  Group: SrcInfo
  Data: electronic
– Name: URL
  Label: Access URL
  Group: URL
  Data: <link linkTarget="URL" linkTerm="https://research.chalmers.se/publication/523192" linkWindow="_blank">https://research.chalmers.se/publication/523192</link><br /><link linkTarget="URL" linkTerm="https://research.chalmers.se/publication/519924" linkWindow="_blank">https://research.chalmers.se/publication/519924</link><br /><link linkTarget="URL" linkTerm="https://research.chalmers.se/publication/522115" linkWindow="_blank">https://research.chalmers.se/publication/522115</link><br /><link linkTarget="URL" linkTerm="https://research.chalmers.se/publication/523192/file/523192_Fulltext.pdf" linkWindow="_blank">https://research.chalmers.se/publication/523192/file/523192_Fulltext.pdf</link>
PLink https://erproxy.cvtisr.sk/sfx/access?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsswe&AN=edsswe.oai.research.chalmers.se.3dfdf500.3c39.4580.b662.9fd37d486eb3
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1364/JOCN.402884
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
        StartPage: A144
    Subjects:
      – SubjectFull: Efficiency
        Type: general
      – SubjectFull: Economic and social effects
        Type: general
      – SubjectFull: Learning systems
        Type: general
      – SubjectFull: Dimensionality reduction
        Type: general
      – SubjectFull: Fiber optic networks
        Type: general
      – SubjectFull: Network architecture
        Type: general
      – SubjectFull: Semi-supervised learning
        Type: general
      – SubjectFull: Infrastructure as a service (IaaS)
        Type: general
      – SubjectFull: Optical communication
        Type: general
    Titles:
      – TitleFull: Optical Network Security Management: Requirements, Architecture and Efficient Machine Learning Models for Detection of Evolving Threats [Invited]
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Furdek Prekratic, Marija
      – PersonEntity:
          Name:
            NameFull: Natalino Da Silva, Carlos
      – PersonEntity:
          Name:
            NameFull: Giglio, Andrea Di
      – PersonEntity:
          Name:
            NameFull: Schiano, Marco
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2021
          Identifiers:
            – Type: issn-print
              Value: 19430620
            – Type: issn-print
              Value: 19430639
            – Type: issn-locals
              Value: SWEPUB_FREE
            – Type: issn-locals
              Value: CTH_SWEPUB
          Numbering:
            – Type: volume
              Value: 13
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Skydda optiska kommunikationsnätverk från cyber-säkerhetsattacker Journal of Optical Communications and Networking
              Type: main
ResultId 1