Hybrid intrusion detection system for wireless IoT networks using deep learning algorithm-Reference-Cited by-同舟云学术

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Hybrid intrusion detection system for wireless IoT networks using deep learning algorithm

Published:2022-09 Issue: Volume:102 Page:108190
ISSN:0045-7906
Container-title:Computers and Electrical Engineering
language:en
Short-container-title:Computers and Electrical Engineering

Author:

Simon Judy,Kapileswar N.,Polasi Phani Kumar,Elaveini M. Aarthi

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,General Computer Science,Control and Systems Engineering

Reference25 articles.

1. A machine learning based IoT for providing an intrusion detection system for security;Atul;Microprocess Microsyst,2021

2. A critical review of practices and challenges in intrusion detection systems for IoT: toward universal and resilient systems;Benkhelifa;IEEE Commun Surv Tut,2018

3. Intrusion detection protocols in wireless sensor networks integrated to internet of things deployment: survey and future challenges;Pundir;IEEE Access,2020

4. Security of the internet of things: vulnerabilities, attacks, and countermeasures;Butun;IEEE Commun Surv Tut,2020

5. Intrusion detection systems in the Internet of things: a comprehensive investigation;Hajiheidari;Comput Netw,2019

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2. Evolving cybersecurity frontiers: A comprehensive survey on concept drift and feature dynamics aware machine and deep learning in intrusion detection systems;Engineering Applications of Artificial Intelligence;2024-11

3. Integrating deep learning and metaheuristics algorithms for blockchain-based reassurance data management in the detection of malicious IoT nodes;Peer-to-Peer Networking and Applications;2024-09-05

4. Deep learning based network intrusion detection system: a systematic literature review and future scopes;International Journal of Information Security;2024-08-02

5. MP-GUARD: A novel multi-pronged intrusion detection and mitigation framework for scalable SD-IoT networks using cooperative monitoring, ensemble learning, and new P4-extracted feature set;Computers and Electrical Engineering;2024-08

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