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DGA Detection Using Similarity-Preserving Bloom Encodings

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In
Proceedings of the 2023 European Interdisciplinary Cybersecurity Conference / Edited by Aleksandra Mileva, Steffen Wendzel, Virginia Franqueira, Seiten/Artikel-Nr: 116-120

Konferenz/Event:European Interdisciplinary Cybersecurity Conference , Stavanger , Norway , EICC 2023 , 2023-06-14 - 2023-06-15

ImpressumNew York,NY,United States : Association for Computing Machinery

Umfang116-120

ISBN978-1-4503-9829-9

Weitere Reihe: ACM digital library

Online
DOI: 10.18154/RWTH-2023-05957
DOI: 10.1145/3590777.3590795

URL: https://publications.rwth-aachen.de/record/959958/files/959958.pdf

Einrichtungen

  1. Lehrstuhl für Informatik 5 (Informationssysteme und Datenbanken) (124510)
  2. Fachgruppe Informatik (120000)

Projekte

  1. SAPPAN - Sharing and Automation for Privacy Preserving Attack Neutralization (833418) (833418)
  2. CyberSEAS - CyberSEAS: Cyber Securing Energy dAta Services (101020560) (101020560)

Inhaltliche Beschreibung (Schlagwörter)
Bloom encoding (frei) ; DGA detection (frei) ; cybersecurity (frei) ; machine learning (frei) ; privacy (frei) ; privacy-preserving data publishing (frei) ; sanitization (frei)

OpenAccess:
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Dokumenttyp
Contribution to a book/Contribution to a conference proceedings

Format
online

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85161406377
WOS Core Collection: WOS:001124185500018

Interne Identnummern
RWTH-2023-05957
Datensatz-ID: 959958

Beteiligte Länder
Germany

 GO


Creative Commons Attribution CC BY 4.0 ; OpenAccess

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 Record created 2023-06-19, last modified 2024-02-05


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