A secure edge computing model using machine learning and IDS to detect and isolate intruders-Reference-Cited by-同舟云学术

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A secure edge computing model using machine learning and IDS to detect and isolate intruders

Published:2024-06 Issue: Volume:12 Page:102597
ISSN:2215-0161
Container-title:MethodsX
language:en
Short-container-title:MethodsX

Author:

Mahadevappa Poornima,Murugesan Raja Kumar,Al-amri Redhwan,Thabit Reema,Al-Ghushami Abdullah Hussein,Alkawsi Gamal

Funder

Qatar National Library

Publisher

Elsevier BV

Reference47 articles.

1. “statistic_id1259878_total-global-edge-enabled-iot-devices-2020-2030-by-market.pdf 2023”.

2. Edge-detect: edge-centric network intrusion detection using deep neural network;Singh,2021

3. An overview of Fog computing and its security issues;Stojmenovic;Concurr. Comput. Pract. Exp.,2016

4. A flexible SDN-based architecture for identifying and mitigating low-rate DDoS attacks using machine learning;Perez-Diaz;IEEE Access,2020

5. Security and privacy in fog computing: challenges;Mukherjee;IEEE Access,2017

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Towards secure IoT networks: A comprehensive study of metaheuristic algorithms in conjunction with CNN using a self-generated dataset;MethodsX;2024-06

2. TinyIDS - An IoT Intrusion Detection System by Tiny Machine Learning;Lecture Notes in Computer Science;2024

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