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Optimizing Filter-Based Feature Selection Method Flow for Intrusion Detection System

https://doi.org/10.3390/electronics9122114

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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-540-77226-2_19openalex-snapshot

Filter Methods for Feature Selection – A Comparative Study

inferredcites →https://doi.org/10.1007/978-3-642-02478-8openalex-snapshot

Bio-Inspired Systems: Computational and Ambient Intelligence

inferredcites →https://doi.org/10.1007/s00500-017-2635-2openalex-snapshot

An IWD-based feature selection method for intrusion detection system

inferredcites →https://doi.org/10.1007/s12083-017-0630-0openalex-snapshot

Survey on SDN based network intrusion detection system using machine learning approaches

inferredcites →https://doi.org/10.1007/s41650-017-0033-7openalex-snapshot

Feature selection techniques for intrusion detection using non-bio-inspired and bio-inspired optimization algorithms

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.eswa.2020.113249openalex-snapshot

A feature selection algorithm for intrusion detection system based on Pigeon Inspired Optimizer

inferredcites →https://doi.org/10.1049/iet-com.2019.0502openalex-snapshot

Improved intrusion detection method for communication networks using association rule mining and artificial neural networks

inferredcites →https://doi.org/10.1088/1742-6596/1192/1/012018openalex-snapshot

Improving AdaBoost-based Intrusion Detection System (IDS) Performance on CIC IDS 2017 Dataset

inferredcites →https://doi.org/10.1109/access.2019.2893871openalex-snapshot

Introducing Deep Learning Self-Adaptive Misuse Network Intrusion Detection Systems

inferredcites →https://doi.org/10.1109/access.2020.2980136openalex-snapshot

An Intrusion Detection Method Using Few-Shot Learning

inferredcites →https://doi.org/10.1109/access.2020.2986217openalex-snapshot

An Efficient Anomaly Intrusion Detection Method With Feature Selection and Evolutionary Neural Network

inferredcites →https://doi.org/10.1109/access.2020.3009843openalex-snapshot

CICIDS-2017 Dataset Feature Analysis With Information Gain for Anomaly Detection

inferredcites →https://doi.org/10.1109/bigdata.2017.8258163openalex-snapshot

A filter-based feature selection model for anomaly-based intrusion detection systems

inferredcites →https://doi.org/10.1109/comst.2018.2847722openalex-snapshot

A Detailed Investigation and Analysis of Using Machine Learning Techniques for Intrusion Detection

inferredcites →https://doi.org/10.1109/conecct50063.2020.9198349openalex-snapshot

A Feature Selection Comparative Study for Web Phishing Datasets

inferredcites →https://doi.org/10.1109/cqr47547.2020.9101394openalex-snapshot

Data Processing and Model Selection for Machine Learning-based Network Intrusion Detection

inferredcites →https://doi.org/10.1109/cspa48992.2020.9068725openalex-snapshot

A Hybrid Anomaly Classification with Deep Learning (DL) and Binary Algorithms (BA) as Optimizer in the Intrusion Detection System (IDS)

inferredcites →https://doi.org/10.1109/icccc.2016.7496749openalex-snapshot

Comparison of wrapper and filter feature selection algorithms on human activity recognition

inferredcites →https://doi.org/10.1109/icmla.2019.00206openalex-snapshot

An Intrusion Detection System for Multi-class Classification Based on Deep Neural Networks

inferredcites →https://doi.org/10.1109/ictc49638.2020.9123302openalex-snapshot

An Efficient Traffic Classification Scheme Using Embedded Feature Selection and LightGBM

inferredcites →https://doi.org/10.1109/ubmk.2017.8093538openalex-snapshot

A feature selection algorithm for IDS

inferredcites →https://doi.org/10.1155/2019/8460934openalex-snapshot

A Hybrid Approach Using Oversampling Technique and Cost‐Sensitive Learning for Bankruptcy Prediction

inferredcites →https://doi.org/10.1186/s42400-020-00052-8openalex-snapshot

Cyber risk at the edge: current and future trends on cyber risk analytics and artificial intelligence in the industrial internet of things and industry 4.0 supply chains

inferredcites →https://doi.org/10.2307/2529310openalex-snapshot

The Measurement of Observer Agreement for Categorical Data

inferredcites →https://doi.org/10.26599/bdma.2020.9020005openalex-snapshot

Novel and efficient randomized algorithms for feature selection

inferredcites →https://doi.org/10.3390/app10114014openalex-snapshot

The Elephant in the Machine: Proposing a New Metric of Data Reliability and its Application to a Medical Case to Assess Classification Reliability

inferredcites →https://doi.org/10.3390/app9071392openalex-snapshot

Network Intrusion Detection Based on Novel Feature Selection Model and Various Recurrent Neural Networks

inferredcites →https://doi.org/10.3390/app9204396openalex-snapshot

Machine Learning and Deep Learning Methods for Intrusion Detection Systems: A Survey

inferredcites →https://doi.org/10.3390/electronics8030322openalex-snapshot

Features Dimensionality Reduction Approaches for Machine Learning Based Network Intrusion Detection

What points at this work

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

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Semiconductor Manufacturing Final Test Yield Prediction Using Regression with Genetic Algorithm-Based Feature Selection

inferred← citeshttps://doi.org/10.1007/978-3-031-73699-5_9openalex-snapshot

ConFlow: Contrast Network Flow Improving Class-Imbalanced Learning in Network Intrusion Detection

inferred← citeshttps://doi.org/10.1007/978-981-99-0609-3_37openalex-snapshot

PCB-LGBM: A Hybrid Feature Selection by Pearson Correlation and Boruta-LGBM for Intrusion Detection Systems

inferred← citeshttps://doi.org/10.1007/978-981-99-7254-8_20openalex-snapshot

A Privacy-Preserving Evolutionary Computation Framework for Feature Selection

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A2N-SFS: an advanced statistical adaptive feature selection method for enhancing intrusion detection systems in IoT systems

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Building robust lightweight network intrusion detection: a multi-pronged approach with DSSTE and deep learning for securing edge-enabled industrial IoT applications

inferred← citeshttps://doi.org/10.1007/s10586-025-05219-xopenalex-snapshot

Explainable AI for enhancing IDS against advanced persistent kill chain

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Attack Detection in IoT Network Using Support Vector Machine and Improved Feature Selection Technique

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CVS-FLN: a novel IoT-IDS model based on metaheuristic feature selection and neural network classification model

inferred← citeshttps://doi.org/10.1007/s11042-024-19962-7openalex-snapshot

Stacked autoencoder with weighted loss function for intrusion detection in IoT application

inferred← citeshttps://doi.org/10.1007/s11227-024-06021-zopenalex-snapshot

Securing IoT networks in cloud computing environments: a real-time IDS

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A hybrid machine learning approach for feature selection in designing intrusion detection systems (IDS) model for distributed computing networks

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Intrusion Detection System for Network Security Using Novel Adaptive Recurrent Neural Network-Based Fox Optimizer Concept

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Robust network anomaly detection using ensemble learning approach and explainable artificial intelligence (XAI)

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BiRNN-SA: Context-aware malicious network traffic detection using self-attentive bidirectional RNNs

inferred← citeshttps://doi.org/10.1063/5.0119308openalex-snapshot

Comparison between machine learning and deep learning for intrusion detection

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An Advanced Intrusion Detection System for IIoT Based on GA and Tree Based Algorithms

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Improved Poverty Tracking and Targeting in Jordan Using Feature Selection and Machine Learning

inferred← citeshttps://doi.org/10.1109/access.2022.3213937openalex-snapshot

Tier-Based Optimization for Synthesized Network Intrusion Detection System

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Shining New Light on Useful Features for Network Intrusion Detection Algorithms

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Ensemble Based Feature Selection Technique For Flow Based Intrusion Detection System

inferred← citeshttps://doi.org/10.1109/icciaa68481.2026.11543831openalex-snapshot

Intrusion Detection and Attack Classification in IoT Networks Using Machine Learning

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MHCFNN: Multihead Attenuated Neuro-Fuzzy based Deep Learning Model for Cybersecurity in Internet of Things

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Effects of Un targeted Adversarial Attacks on Deep Learning Methods

inferred← citeshttps://doi.org/10.1109/rtucon67996.2025.11415103openalex-snapshot

Lightweight Machine Learning-based Intrusion Detection Under Class Imbalance in Smart Grids

inferred← citeshttps://doi.org/10.1109/tnsm.2024.3390180openalex-snapshot

A Semantic Detection Method for Network Flows With Global and Generalized Nature

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Traffic-Based Validation of Virtualized Communication Networks

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An Optimized and Hybrid Framework for Image Processing Based Network Intrusion Detection System

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IoT Intrusion Detection Using Machine Learning with a Novel High Performing Feature Selection Method

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A Study on the Psychology of Social Engineering-Based Cyberattacks and Existing Countermeasures

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Comprehensive Review of UAV Detection, Security, and Communication Advancements to Prevent Threats

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