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Optimal feature selection for machine learning based intrusion detection system by exploiting attribute dependence

https://doi.org/10.1016/j.matpr.2021.04.643

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What this work says

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

inferredcites →https://doi.org/10.1002/ett.4150openalex-snapshot

Network intrusion detection system: A systematic study of machine learning and deep learning approaches

inferredcites →https://doi.org/10.1007/978-3-030-38040-3_31openalex-snapshot

Machine Learning Techniques: A Survey

inferredcites →https://doi.org/10.1007/978-81-322-2529-4_51openalex-snapshot

Analysis of Machine Learning Techniques Based Intrusion Detection Systems

inferredcites →https://doi.org/10.1007/s12652-020-02014-xopenalex-snapshot

A survey of neural networks usage for intrusion detection systems

inferredcites →https://doi.org/10.1016/j.eswa.2017.07.005openalex-snapshot

A feature reduced intrusion detection system using ANN classifier

inferredcites →https://doi.org/10.1016/j.ipm.2020.102240openalex-snapshot

FS-MLC: Feature selection for multi-label classification using clustering in feature space

inferredcites →https://doi.org/10.1016/j.knosys.2019.105124openalex-snapshot

Deep learning approaches for anomaly-based intrusion detection systems: A survey, taxonomy, and open issues

inferredcites →https://doi.org/10.1016/j.neucom.2017.11.077openalex-snapshot

Feature selection in machine learning: A new perspective

inferredcites →https://doi.org/10.1016/j.patcog.2020.107663openalex-snapshot

Pairwise dependence-based unsupervised feature selection

inferredcites →https://doi.org/10.1016/j.procs.2015.04.191openalex-snapshot

Intrusion Detection System (IDS): Anomaly Detection Using Outlier Detection Approach

inferredcites →https://doi.org/10.1016/j.procs.2016.05.203openalex-snapshot

Feature Selection Using Relative Fuzzy Entropy and Ant Colony Optimization Applied to Real-time Intrusion Detection System

inferredcites →https://doi.org/10.1088/1742-6596/1732/1/012023openalex-snapshot

A stable feature selection method based on relevancy and redundancy

inferredcites →https://doi.org/10.1088/1757-899x/1013/1/012038openalex-snapshot

Comparative analysis of Machine Learning algorithms for Intrusion Detection

inferredcites →https://doi.org/10.1109/access.2018.2882545openalex-snapshot

Research on the Fusion of Dependent Evidence Based on Mutual Information

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/calcon49167.2020.9106516openalex-snapshot

Mutually Informed Correlation Coefficient (MICC) - a New Filter Based Feature Selection Method

inferredcites →https://doi.org/10.1109/ibigdelft.2018.8625278openalex-snapshot

Deep Learning in Intrusion Detection Systems

inferredcites →https://doi.org/10.1109/icitst.2016.7856705openalex-snapshot

Machine learning classification model for Network based Intrusion Detection System

inferredcites →https://doi.org/10.1109/icoei.2019.8862784openalex-snapshot

Machine Learning Based Intrusion Detection System

inferredcites →https://doi.org/10.1109/sisy.2017.8080566openalex-snapshot

Evaluation of machine learning algorithms for intrusion detection system

inferredcites →https://doi.org/10.2991/ijcis.d.210105.001openalex-snapshot

Intrusion Detection Systems, Issues, Challenges, and Needs

inferredcites →https://doi.org/10.5120/ijca2016908592openalex-snapshot

Anomaly based IDS using Backpropagation Neural Network

What points at this work

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

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Protocol-Based Multi-Ensemble Classifier for Intrusion Detection Using Packet Header Fields

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Machine Learning Techniques for Sentimental Analysis

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BSLnO: Multi‐agent based distributed intrusion detection system using Bat Sea Lion Optimization‐based hybrid deep learning approach

inferred← citeshttps://doi.org/10.1007/978-3-030-97196-0_43openalex-snapshot

Significance of Dimensionality Reduction in Intrusion Detection Dataset

inferred← citeshttps://doi.org/10.1007/978-3-031-50590-4_20openalex-snapshot

Training and Classification Techniques in Intrusion Detection Systems Based on Network Anomalies Comparative Study

inferred← citeshttps://doi.org/10.1007/978-981-99-2100-3_32openalex-snapshot

Hyperparameter Tuning for Edge-IIoT Intrusion Detection Using SMOTE

inferred← citeshttps://doi.org/10.1007/s10489-023-05176-1openalex-snapshot

A multi-constraint transfer approach with additional auxiliary domains for IoT intrusion detection under unbalanced samples distribution

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Machine learning-driven approaches in electrochemical CO2 reduction: Bridging the gap between data and sustainable catalysis

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On resource consumption of machine learning in communications network security

inferred← citeshttps://doi.org/10.1016/j.compeleceng.2025.110627openalex-snapshot

A novel feature engineering method for network anomaly detection

inferred← citeshttps://doi.org/10.1016/j.cose.2023.103567openalex-snapshot

APELID: Enhancing real-time intrusion detection with augmented WGAN and parallel ensemble learning

inferred← citeshttps://doi.org/10.1016/j.jnca.2023.103735openalex-snapshot

AI-powered intrusion detection in large-scale traffic networks based on flow sensing strategy and parallel deep analysis

inferred← citeshttps://doi.org/10.1049/wss2.12100openalex-snapshot

Intrusion detection in cluster‐based wireless sensor networks: Current issues, opportunities and future research directions

inferred← citeshttps://doi.org/10.1080/08839514.2025.2539396openalex-snapshot

A Two-Phase Feature Selection Framework for Intrusion Detection System: Balancing Relevance and Computational Efficiency (2P-FSID)

inferred← citeshttps://doi.org/10.1080/21642583.2025.2460429openalex-snapshot

AccFIT-IDS: accuracy-based feature inclusion technique for intrusion detection system

inferred← citeshttps://doi.org/10.1088/2631-8695/adf0c9openalex-snapshot

Smart network intrusion detection system using stacked ensemble learning and data analytics

inferred← citeshttps://doi.org/10.1109/aca57612.2023.10346864openalex-snapshot

Detection of DDoS Attacks in Software-Defined Networks Based on Majority Voting-Average for Feature Selection and Machine Learning Approaches

inferred← citeshttps://doi.org/10.1109/iscas58744.2024.10558079openalex-snapshot

Case Study: Understanding Internet Anomalies

inferred← citeshttps://doi.org/10.1109/smc53992.2023.10394194openalex-snapshot

BGP Features and Classification of Internet Worms and Ransomware Attacks

inferred← citeshttps://doi.org/10.1109/smc54092.2024.10831186openalex-snapshot

Internet Outages During Times of Conflict

inferred← citeshttps://doi.org/10.1155/2022/6591140openalex-snapshot

Network Intrusion Detection Method Based on FCWGAN and BiLSTM

inferred← citeshttps://doi.org/10.20935/acadbiol7324openalex-snapshot

Feature selection in single-cell RNA sequencing data: a comprehensive evaluation

inferred← citeshttps://doi.org/10.32604/cmc.2023.046478openalex-snapshot

Strengthening Network Security: Deep Learning Models for Intrusion Detection with Optimized Feature Subset and Effective Imbalance Handling

inferred← citeshttps://doi.org/10.32604/cmc.2024.059271openalex-snapshot

IoT-CDS: Internet of Things Cyberattack Detecting System Based on Deep Learning Models

inferred← citeshttps://doi.org/10.3390/app13010030openalex-snapshot

An Ensemble-Based Machine Learning Approach for Cyber-Attacks Detection in Wireless Sensor Networks

inferred← citeshttps://doi.org/10.3390/app13042079openalex-snapshot

SFCWGAN-BiTCN with Sequential Features for Malware Detection

inferred← citeshttps://doi.org/10.3390/electronics12204289openalex-snapshot

IoT Intrusion Detection System Based on Machine Learning

inferred← citeshttps://doi.org/10.37391/090302openalex-snapshot

Investigating the Impact of Feature Reduction Through Information Gain and Correlation on the Performance of Error Back Propagation Based IDS

inferred← citeshttps://doi.org/10.4018/978-1-6684-8127-1.ch006openalex-snapshot

Feature Engineering and Computer Vision for Cybersecurity

inferred← citeshttps://doi.org/10.55041/ijsrem29818openalex-snapshot

Enhancing Intrusion Detection through Unsupervised Deep Learning Models

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