Machine Learning Based Intrusion Detection Systems for IoT Applications
Sign Up to like & getrecommendations! Published in 2020 at "Wireless Personal Communications"
DOI: 10.1007/s11277-019-06986-8
Abstract: Internet of Things (IoT) and its applications are the most popular research areas at present. The characteristics of IoT on one side make it easily applicable to real-life applications, whereas on the other side expose… read more here.
Keywords: machine learning; iot applications; detection systems; intrusion detection ... See more keywords
An improved bio-inspired based intrusion detection model for a cyberspace
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DOI: 10.1080/23311916.2020.1859667
Abstract: Bio-inspired intrusion detection solutions provide better detection accuracy than conventional solutions in securing cyberspace. However, existing bio-inspired anomaly-based intrusion detection sys... read more here.
Keywords: detection; bio inspired; cyberspace; intrusion detection ... See more keywords
Anomaly-Based Intrusion Detection From Network Flow Features Using Variational Autoencoder
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DOI: 10.1109/access.2020.3001350
Abstract: The rapid increase in network traffic has recently led to the importance of flow-based intrusion detection systems processing a small amount of traffic data. Furthermore, anomaly-based methods, which can identify unknown attacks are also integrated… read more here.
Keywords: based intrusion; variational autoencoder; network; flow ... See more keywords
Enhancing Security in LLNs Using a Hybrid Trust-Based Intrusion Detection System for RPL
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DOI: 10.1109/access.2024.3391918
Abstract: An extensive worldwide network known as the Internet of Things (IoT) links different electronic devices and facilitates easy communication and group work. This interdependency is especially apparent in Low Power and Lossy Networks (LLNs), where… read more here.
Keywords: trust based; intrusion detection; trust; detection system ... See more keywords
A Hybrid Lightweight Deep Learning-Based Intrusion Detection Approach in IoT Utilizing Feature Selection & Explainable Artificial Intelligence
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DOI: 10.1109/access.2025.3630753
Abstract: Due to the resource constraints of IoT devices, standard cryptographic-based intrusion detection techniques are ineffective in real-world IoT environments. This study presents DL-IID, a lightweight deep learning-based framework for IoT intrusion detection. The model integrates… read more here.
Keywords: intrusion detection; intrusion; lightweight deep; iot ... See more keywords
Semisupervised Federated-Learning-Based Intrusion Detection Method for Internet of Things
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3175918
Abstract: Federated learning (FL) has become an increasingly popular solution for intrusion detection to avoid data privacy leakage in Internet of Things (IoT) edge devices. Existing FL-based intrusion detection methods, however, suffer from three limitations: 1)… read more here.
Keywords: intrusion detection; based intrusion; federated learning; detection ... See more keywords
Histogram-Based Intrusion Detection and Filtering Framework for Secure and Safe In-Vehicle Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2021.3088998
Abstract: In this paper, we propose H-IDFS, a Histogram-based Intrusion Detection and Filtering framework, which assembles the CAN packets into windows, and computes their corresponding histograms. The latter are fed to a multi-class IDS classifier to… read more here.
Keywords: intrusion detection; based intrusion; histogram based; detection filtering ... See more keywords
The Evolution of Federated Learning-Based Intrusion Detection and Mitigation: A Survey
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Network and Service Management"
DOI: 10.1109/tnsm.2022.3177512
Abstract: In 2016, Google introduced the concept of Federated Learning (FL), enabling collaborative Machine Learning (ML). FL does not share local data but ML models, offering applications in diverse domains. This paper focuses on the application… read more here.
Keywords: intrusion detection; based intrusion; federated learning; survey ... See more keywords
Implementation of Lightweight Machine Learning-Based Intrusion Detection System on IoT Devices of Smart Homes
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DOI: 10.3390/fi16060200
Abstract: Smart home devices, also known as IoT devices, provide significant convenience; however, they also present opportunities for attackers to jeopardize homeowners’ security and privacy. Securing these IoT devices is a formidable challenge because of their… read more here.
Keywords: intrusion detection; machine learning; learning based; based intrusion ... See more keywords
An Explainable AI-Based Intrusion Detection System for DNS Over HTTPS (DoH) Attacks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.36227/techrxiv.17696972
Abstract: Over the past few years, Domain Name Service (DNS) remained a prime target for hackers as it enables them to gain first entry into networks and gain access to data for exfiltration. Although the DNS… read more here.
Keywords: dns https; based intrusion; explainable based; https ... See more keywords