has been cited by the following article(s):
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[1]
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Unsupervised Correlation-Based Classification of IoT Malware for Consumer Devices
2026 IEEE International Conference on Consumer Electronics (ICCE),
2026
DOI:10.1109/ICCE67443.2026.11449764
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[2]
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Computer Security. ESORICS 2025 International Workshops
Lecture Notes in Computer Science,
2026
DOI:10.1007/978-3-032-16165-9_29
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[3]
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CIC-YNU-IoTMal: A comprehensive multilayer dataset for static and dynamic analysis of IoT malware behavior
Information Systems,
2026
DOI:10.1016/j.is.2026.102722
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[4]
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A Hierarchical Classification Methodology for Online Key Courses on Ideological and Cultural Cultivation of Higher Education Students: A Perspective from Medical Colleges and Universities
Journal of Higher Vocational Education,
2026
DOI:10.62517/jhve.202616312
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[5]
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A multimodal feature fusion-driven framework for IoT malware classification
Discover Computing,
2026
DOI:10.1007/s10791-026-10523-0
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[6]
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Towards Lightweight Hybrid Deep Learning Approach to Malware Detection Enhancement For IoT Based Systems
2025 8th International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech),
2025
DOI:10.1109/IEMENTech65115.2025.10959623
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[7]
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Malware Detection with AI: A Comprehensive Review of Trends and Challenges with Future Directions
Peer-to-Peer Networking and Applications,
2025
DOI:10.1007/s12083-025-02112-7
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