IOT threats detection using few shots learning
Existing IoT threat detection methods lack robustness due to the diverse array of potential attack vectors. Currently, most methods are trained and tested using simulated datasets and do not perform well with unseen samples in real-world applications. In this project, we propose a novel few short...
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| Format: | Final Year Project / Dissertation / Thesis |
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2024
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| Online Access: | http://eprints.utar.edu.my/6634/ http://eprints.utar.edu.my/6634/1/fyp_CS_2024_CCH.pdf |