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A Machine Learning Based Two-Stage Wi-Fi Network Intrusion Detection System

https://doi.org/10.3390/electronics9101689

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-06158-6_10openalex-snapshot

Intrusion Detection for WiFi Network: A Deep Learning Approach

inferredcites →https://doi.org/10.1007/978-981-13-1444-5openalex-snapshot

Network Intrusion Detection using Deep Learning

inferredcites →https://doi.org/10.1007/978-981-13-1444-5_6openalex-snapshot

Deep Feature Learning

inferredcites →https://doi.org/10.1007/bf00058655openalex-snapshot

Bagging predictors

inferredcites →https://doi.org/10.1007/s11721-007-0002-0openalex-snapshot

Particle swarm optimization

inferredcites →https://doi.org/10.1016/j.asoc.2013.03.021openalex-snapshot

Modified binary PSO for feature selection using SVM applied to mortality prediction of septic patients

inferredcites →https://doi.org/10.1016/j.comnet.2020.107247openalex-snapshot

Building an efficient intrusion detection system based on feature selection and ensemble classifier

inferredcites →https://doi.org/10.1016/j.cose.2020.101752openalex-snapshot

A deep learning method with wrapper based feature extraction for wireless intrusion detection system

inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot

Random Forests

inferredcites →https://doi.org/10.1109/access.2020.2985089openalex-snapshot

IMPACT: Impersonation Attack Detection via Edge Computing Using Deep Autoencoder and Feature Abstraction

inferredcites →https://doi.org/10.1109/access.2020.2988359openalex-snapshot

An Explainable Machine Learning Framework for Intrusion Detection Systems

inferredcites →https://doi.org/10.1109/ccece.2016.7726677openalex-snapshot

Machine learning techniques for intrusion detection on public dataset

inferredcites →https://doi.org/10.1109/cec.2012.6256617openalex-snapshot

New fitness functions in binary particle swarm optimisation for feature selection

inferredcites →https://doi.org/10.1109/cisda.2009.5356528openalex-snapshot

A detailed analysis of the KDD CUP 99 data set

inferredcites →https://doi.org/10.1109/comst.2015.2402161openalex-snapshot

Intrusion Detection in 802.11 Networks: Empirical Evaluation of Threats and a Public Dataset

inferredcites →https://doi.org/10.1109/iecon.2018.8591457openalex-snapshot

An Adversarial Approach for Explainable AI in Intrusion Detection Systems

inferredcites →https://doi.org/10.1109/milcis.2015.7348942openalex-snapshot

UNSW-NB15: a comprehensive data set for network intrusion detection systems (UNSW-NB15 network data set)

inferredcites →https://doi.org/10.1109/nca.2018.8548315openalex-snapshot

An Ensemble Learning Based Wi-Fi Network Intrusion Detection System (WNIDS)

inferredcites →https://doi.org/10.1109/tifs.2017.2762828openalex-snapshot

Deep Abstraction and Weighted Feature Selection for Wi-Fi Impersonation Detection

inferredcites →https://doi.org/10.1109/vtcspring.2019.8746576openalex-snapshot

A Semi-Supervised Learning Approach to IEEE 802.11 Network Anomaly Detection

inferredcites →https://doi.org/10.1109/wcnc.2017.7925567openalex-snapshot

IEEE 802.11 Network Anomaly Detection and Attack Classification: A Deep Learning Approach

inferredcites →https://doi.org/10.3390/electronics9030530openalex-snapshot

A Two-Level Flow-Based Anomalous Activity Detection System for IoT Networks

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Explainable Anomaly Detection in IoT Networks

inferred← citeshttps://doi.org/10.1007/978-3-031-77029-6_11openalex-snapshot

Intelligent Machine Learning for Cybersecurity: Anomaly Detection in Network Intrusion Systems and Beyond

inferred← citeshttps://doi.org/10.1007/978-981-92-1243-9_12openalex-snapshot

Mapping the Landscape of Network Intrusion Detection: Trends, Techniques and Future Research

inferred← citeshttps://doi.org/10.1007/978-981-97-0767-6_43openalex-snapshot

A Study of Cybersecurity in Industrial Internet of Things (IIoT)

inferred← citeshttps://doi.org/10.1007/s10586-025-05326-9openalex-snapshot

L-xaids: A LIME-based eXplainable AI framework for intrusion detection systems

inferred← citeshttps://doi.org/10.1007/s10586-025-05601-9openalex-snapshot

A novel fine-grained intelligent framework for mitigating cyber-attacks through hybrid chaos-triggered tasmanian devil feature optimization and feedforward learning networks

inferred← citeshttps://doi.org/10.1007/s10791-025-09678-zopenalex-snapshot

A novel integration of multi-stocked gated variant recurrent units and Kolmogorov-Arnold tuned deep training networks for anchoring the intrusion detection against computer attacks

inferred← citeshttps://doi.org/10.1007/s10922-026-10055-4openalex-snapshot

Optimized Feature Selection Using Rough Sets for Intrusion Detection in 802.11 Wireless Networks

inferred← citeshttps://doi.org/10.1007/s11276-023-03516-0openalex-snapshot

Lightweight real-time WiFi-based intrusion detection system using LightGBM

inferred← citeshttps://doi.org/10.1016/j.aej.2024.01.073openalex-snapshot

Optimizing intrusion detection using intelligent feature selection with machine learning model

inferred← citeshttps://doi.org/10.1016/j.engappai.2024.109410openalex-snapshot

Advances in artificial intelligence for detecting algorithmically generated domains: Current trends and future prospects

inferred← citeshttps://doi.org/10.1016/j.engappai.2025.110145openalex-snapshot

Explainable artificial intelligence models in intrusion detection systems

inferred← citeshttps://doi.org/10.1016/j.jisa.2026.104563openalex-snapshot

XAI in cybersecurity: A survey on techniques, challenges, and future directions

inferred← citeshttps://doi.org/10.1049/ntw2.12128openalex-snapshot

Meta‐analysis and systematic review for anomaly network intrusion detection systems: Detection methods, dataset, validation methodology, and challenges

inferred← citeshttps://doi.org/10.1093/comjnl/bxac119openalex-snapshot

An Efficient Deep Learning Approach To IoT Intrusion Detection

inferred← citeshttps://doi.org/10.1109/access.2021.3061609openalex-snapshot

Empirical Evaluation of Attacks Against IEEE 802.11 Enterprise Networks: The AWID3 Dataset

inferred← citeshttps://doi.org/10.1109/access.2022.3183597openalex-snapshot

Pick Quality Over Quantity: Expert Feature Selection and Data Preprocessing for 802.11 Intrusion Detection Systems

inferred← citeshttps://doi.org/10.1109/access.2022.3204171openalex-snapshot

Explainable Artificial Intelligence in CyberSecurity: A Survey

inferred← citeshttps://doi.org/10.1109/access.2024.3380014openalex-snapshot

Intrusion Detection System for Wireless Sensor Networks: A Machine Learning Based Approach

inferred← citeshttps://doi.org/10.1109/compas67506.2025.11381654openalex-snapshot

Explainable AI Framework for Multiclass Attack Classification in Wireless Network Intrusion Detection Systems

inferred← citeshttps://doi.org/10.1109/eurosp57164.2023.00022openalex-snapshot

SoK: Explainable Machine Learning for Computer Security Applications

inferred← citeshttps://doi.org/10.1109/gcon65540.2025.11173344openalex-snapshot

An Approach to Classify Intrusion in IoT System Using Neural Architecture Search

inferred← citeshttps://doi.org/10.1109/globecom48099.2022.10001501openalex-snapshot

RIDS: Real-time Intrusion Detection System for WPA3 enabled Enterprise Networks

inferred← citeshttps://doi.org/10.1109/icacs60934.2024.10473266openalex-snapshot

Cyber Attack Identification System Using Deep Learning

inferred← citeshttps://doi.org/10.1109/icesc57686.2023.10193625openalex-snapshot

Deep Learning with Conditional Generative Adversarial Network Based Intrusion Detection System on Balanced Data

inferred← citeshttps://doi.org/10.1109/icitacee58587.2023.10277350openalex-snapshot

Double Layer Machine Learning for Network Intrusion Detection System on Web Server

inferred← citeshttps://doi.org/10.1109/icitri56423.2022.9970221openalex-snapshot

An Adversarial Approach for Intrusion Detection Using Hybrid Deep Learning Model

inferred← citeshttps://doi.org/10.1109/icssit53264.2022.9716485openalex-snapshot

A Novel Deep Neural Network Model for Computer Network Intrusion Detection Considering Connection Efficiency of Network Systems

inferred← citeshttps://doi.org/10.1109/idap64064.2024.10710835openalex-snapshot

Smart Cyber Defense: Machine Learnig Powered Intrusion Detection in 802.11 Networks

inferred← citeshttps://doi.org/10.1109/iotais67227.2025.11282135openalex-snapshot

Protocol-Aware Continuous Monitoring and Anomaly Detection in Internet of Things Networks

inferred← citeshttps://doi.org/10.1109/isea-isap54304.2021.9689765openalex-snapshot

Explainable Artificial Intelligence in Cybersecurity: A Brief Review

inferred← citeshttps://doi.org/10.1109/lcn58197.2023.10223401openalex-snapshot

Leveraging Explainable AI Methods Towards Identifying Classification Issues on IDS Datasets

inferred← citeshttps://doi.org/10.1109/vtc2023-spring57618.2023.10199490openalex-snapshot

A Gradient Boosted ML Approach to Feature Selection for Wireless Intrusion Detection

inferred← citeshttps://doi.org/10.1111/jtxs.70004openalex-snapshot

Predicting Color Development and Texture Changes in Tomatoes Treated With Hot Water and Exposed to High‐Temperature Ethylene Using Support Vector Regression

inferred← citeshttps://doi.org/10.1371/journal.pone.0306747openalex-snapshot

An investigation of feature reduction, transferability, and generalization in AWID datasets for secure Wi-Fi networks

inferred← citeshttps://doi.org/10.19101/ijatee.2022.10100475openalex-snapshot

Network intrusion detection system using bacterial foraging optimization with random forest

inferred← citeshttps://doi.org/10.32628/ijsrst251368openalex-snapshot

Predictive Maintenance in Leveraging Supervised Machine Learning For Wireless Network Attacks

inferred← citeshttps://doi.org/10.32985/ijeces.15.2.2openalex-snapshot

An Effective Technique to Detect WIFI Unauthorized Access using Deep Belief Network

inferred← citeshttps://doi.org/10.3390/a17060227openalex-snapshot

Explainable AI Frameworks: Navigating the Present Challenges and Unveiling Innovative Applications

inferred← citeshttps://doi.org/10.3390/electronics10141622openalex-snapshot

Comparing Machine Learning Classifiers for Continuous Authentication on Mobile Devices by Keystroke Dynamics

inferred← citeshttps://doi.org/10.3390/electronics10222878openalex-snapshot

Machine Learning and Fuzzy Logic in Electronics: Applying Intelligence in Practice

inferred← citeshttps://doi.org/10.3390/electronics12112355openalex-snapshot

Rule-Based System with Machine Learning Support for Detecting Anomalies in 5G WLANs

inferred← citeshttps://doi.org/10.3390/electronics12173731openalex-snapshot

Transfer and CNN-Based De-Authentication (Disassociation) DoS Attack Detection in IoT Wi-Fi Networks

inferred← citeshttps://doi.org/10.3844/jcssp.2024.442.453openalex-snapshot

Fed-Deep CTRL (Light GBM)-Scalable, Interpretable, and Privacy-Preserving Federated Learning Framework for Wireless Intrusion Detection System

inferred← citeshttps://doi.org/10.4271/2026-26-0617openalex-snapshot

Real-Time Intrusion Detection System (IDS) for Vehicle Networks Using Machine Learning for Predictive Threat Analysis

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Enhanced Cybersecurity for Network Intrusion Detection System Based Artificial Intelligence (AI) Techniques

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Natural Language-Based Explainable Intrusion Detection for Vehicular Networks: Handling CAN and Wi-Fi Attack Vectors

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