Obfuscated Malware Detection and Classification in Network Traffic Leveraging Hybrid Large Language...
Obfuscated Malware Detection and Classification in Network Traffic Leveraging Hybrid Large Language Models and Synthetic Data
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Publisher
Switzerland: MDPI AG
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Language
English
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Publisher
Switzerland: MDPI AG
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Android malware detection remains a critical issue for mobile security. Cybercriminals target Android since it is the most popular smartphone operating system (OS). Malware detection, analysis, and classification have become diverse research areas. This paper presents a smart sensing model based on large language models (LLMs) for developing and cl...
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Full title
Obfuscated Malware Detection and Classification in Network Traffic Leveraging Hybrid Large Language Models and Synthetic Data
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TN_cdi_doaj_primary_oai_doaj_org_article_43bb6e7697eb445494d6dae6ca6de4af
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_43bb6e7697eb445494d6dae6ca6de4af
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ISSN
1424-8220
E-ISSN
1424-8220
DOI
10.3390/s25010202
