Deep Learning Approaches for Intrusion Detection in IoT Environments: A Systematic Literature Review
Open Access
- 1 October 2026
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Internet of Things Journal
- Vol. 13 (20) , 46485-46513
Abstract
No abstract availableThis publication has 61 references indexed in Scilit:
- Transforming security in internet of medical things with advanced deep learning-based intrusion detection frameworksApplied Soft Computing, 2025
- A hybrid software-defined networking approach for enhancing IoT cybersecurity with deep learning and blockchain in smart citiesPeer-to-Peer Networking and Applications, 2025
- A privacy-preserving Self-Supervised Learning-based intrusion detection system for 5G-V2X networksAd Hoc Networks, 2024
- Intrusion detection and prevention in fog based IoT environments: A systematic literature reviewComputer Networks, 2022
- Detection and prevention of man-in-the-middle attack in iot network using regression modelingAdvances in Engineering Software, 2022
- The journal coverage of Web of Science, Scopus and Dimensions: A comparative analysisScientometrics, 2021
- Machine Learning Models for Secure Data Analytics: A taxonomy and threat modelComputer Communications, 2020
- Internet of Things: A survey on machine learning-based intrusion detection approachesComputer Networks, 2019
- Software survey: VOSviewer, a computer program for bibliometric mappingScientometrics, 2009
- Empirical Evidence for Selective Reporting of Outcomes in Randomized TrialsJAMA, 2004