Machine learning based intrusion detection system for IoMT
Author:
Publisher
Springer Science and Business Media LLC
Subject
Strategy and Management,Safety, Risk, Reliability and Quality
Link
https://link.springer.com/content/pdf/10.1007/s13198-023-02119-4.pdf
Reference35 articles.
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2. Agarwal A, Khari M, Singh R (2021) Detection of DDOS attack using deep learning model in cloud storage application. Wireless Pers Commun 127:419–439. https://doi.org/10.1007/s11277-021-08271-z
3. Alabsi BA, Anbar M, Rihan SD (2023) Conditional tabular generative adversarial based intrusion detection system for detecting ddos and dos attacks on the Internet of Things networks. Sensors. https://doi.org/10.3390/s23125644
4. Aldhaheri S, Alghazzawi D, Cheng L, Alzahrani B, Al-Barakati A (2020) DeepDCA: novel network-based detection of iot attacks using artificial immune system. Appl Sci 10(6):85. https://doi.org/10.3390/app10061909
5. Alrashdi I, Alqazzaz A, Alharthi R, Aloufi E, Zohdy MA, Ming H (2019) FBAD: fog-based attack detection for IoT healthcare in smart cities. In 2019 IEEE 10th annual ubiquitous computing, electronics and mobile communication conference (UEMCON), pp 0515–0522. https://doi.org/10.1109/UEMCON47517.2019.8992963
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