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On Machine Learning for Digital Forensics Investigation in Network Traffic

Tundis, Andrea und Cauteruccio, Francesco (2025) On Machine Learning for Digital Forensics Investigation in Network Traffic. In: 21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT 2025), Seiten 1027-1033. IEEE. 21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), 2025-06-09 - 2025-06-11, Lucca, Italy. doi: 10.1109/DCOSS-IoT65416.2025.00155. ISBN 979-8-3315-4372-3. ISSN 2325-2944.

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Kurzfassung

Cybercrime is an ever increasing issue in the modern world. With the growing reliance of individuals, companies and countries on digital infrastructure, more people are exposed to potential attack vectors which cybercriminals can use to extort a ransom, steal data, commit fraud, or cause significant financial damage. To prevent such crimes from occurring, various security measures are being employed. One such measure is network forensics, which focuses on analyzing network traffic data to uncover evidence and information about attacks and detect intrusions. Network forensics has to deal with large, dynamic, and volatile data, which makes performing analysis a challenging task. Machine learning has been proposed to overcome some of the challenges associated with such analysis. This paper aims to give an overview of network forensics and machine learning, present some tools investigators use to perform network forensics, and introduce some results of recent research into the use of machine learning for network forensics. Finally, a brief discussion of current challenges and further research directions is provided.

elib-URL des Eintrags:https://elib.dlr.de/214505/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:On Machine Learning for Digital Forensics Investigation in Network Traffic
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Tundis, AndreaAndrea.Tundis (at) dlr.dehttps://orcid.org/0000-0002-7729-2780185911448
Cauteruccio, Francescofcauteruccio (at) unisa.itNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:2025
Erschienen in:21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT 2025)
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Nein
In ISI Web of Science:Nein
DOI:10.1109/DCOSS-IoT65416.2025.00155
Seitenbereich:Seiten 1027-1033
Verlag:IEEE
ISSN:2325-2944
ISBN:979-8-3315-4372-3
Status:veröffentlicht
Stichwörter:Digital Forensics Investigation, Network Traffic Analysis, Machine Learning, Artificial Intelligence, Cybersecurity.
Veranstaltungstitel:21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT)
Veranstaltungsort:Lucca, Italy
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:9 Juni 2025
Veranstaltungsende:11 Juni 2025
HGF - Forschungsbereich:keine Zuordnung
HGF - Programm:keine Zuordnung
HGF - Programmthema:keine Zuordnung
DLR - Schwerpunkt:Digitalisierung
DLR - Forschungsgebiet:D CPE - Cyberphysisches Engineering
DLR - Teilgebiet (Projekt, Vorhaben):D - urbanModel, D - Digitaler Atlas 2.0
Standort: Rhein-Sieg-Kreis
Institute & Einrichtungen:Institut für den Schutz terrestrischer Infrastrukturen > Digitale Zwillinge von Infrastrukturen
Institut für den Schutz terrestrischer Infrastrukturen
Hinterlegt von: Tundis, Andrea
Hinterlegt am:13 Jun 2025 10:35
Letzte Änderung:13 Jun 2025 10:35

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