An empirical study of problems and evaluation of IoT malware classification label sources

An empirical study of problems and evaluation of IoT malware classification label sources

With the proliferation of malware on IoT devices, research on IoT malicious code has also become more mature. Most studies use learning models to detect or classify malware. Therefore, ensuring high-quality labels for malware samples is crucial to maintaining research accuracy. Researchers typically...

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Bibliografische gegevens
Hoofdauteurs: Tianwei Lei, Jingfeng Xue, Yong Wang, Thar Baker, Zequn Niu
Formaat: Artikel
Taal:English
Gepubliceerd in: Elsevier 2024-01-01
Reeks:Journal of King Saud University: Computer and Information Sciences
Onderwerpen:
Malware classification
Malware label
IoT malware analysis
Anti-Virus engine label
Label tool
Online toegang:http://www.sciencedirect.com/science/article/pii/S1319157823004524

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http://www.sciencedirect.com/science/article/pii/S1319157823004524

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