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Understanding stegomalware in ICS: Attacks and Prevention

dc.contributor.authorEdeh, Natasha
dc.contributor.authorYatagha, Romarick
dc.contributor.authorMejri, Oumayma
dc.contributor.authorWaedt, Karl
dc.contributor.editorKlein, Maike
dc.contributor.editorKrupka, Daniel
dc.contributor.editorWinter, Cornelia
dc.contributor.editorGergeleit, Martin
dc.contributor.editorMartin, Ludger
dc.date.accessioned2024-10-21T18:24:17Z
dc.date.available2024-10-21T18:24:17Z
dc.date.issued2024
dc.description.abstractThis research investigates the growing threat of stego-malware in Industrial Control Systems (ICS), where attackers utilize steganography to embed malicious code covertly. Such attacks pose significant challenges due to their ability to evade traditional detection methods. The study reviews current cybersecurity frameworks and detection techniques, highlighting their strengths and limitations against stego-malware. It explores various detection approaches, including signature-based, anomaly-based, and AI/ML-based methods, assessing their effectiveness within the context of ISO/IEC 27001 and IEC 62443 standards. Case studies such as Havex and Industroyer underscore the real-world impact of stego-malware on ICS infrastructure. The research advocates for enhanced integration of AI and machine learning to bolster steganalysis capabilities, and proposes improvements to existing cybersecurity frameworks to address steganographic threats more effectively. By bridging gaps in current knowledge, this study contributes to advancing cybersecurity measures tailored to protect critical ICS environments against evolving cyber threats.en
dc.identifier.doi10.18420/inf2024_164
dc.identifier.isbn978-3-88579-746-3
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/45141
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2024
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-352
dc.subjectStegomalware
dc.subjectICS
dc.subjectSteganography
dc.subjectAI
dc.subjectML
dc.subjectSteganalysis
dc.titleUnderstanding stegomalware in ICS: Attacks and Preventionen
dc.typeText/Conference Paper
gi.citation.endPage1904
gi.citation.publisherPlaceBonn
gi.citation.startPage1893
gi.conference.date24.-26. September 2024
gi.conference.locationWiesbaden
gi.conference.sessiontitle9th IACS WS'24

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