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Machine Learning-Based Cyberattacks Detection Enhancement in Iot Environments with Imbalanced Data Handling

https://doi.org/10.2139/ssrn.4828295
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Imbalanced Learning
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Securing Internet of Things (IoT) with machine learning
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Security threats and measures in the Internet of Things for smart city infrastructure: A state of art
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Performance Evaluation of Machine Learning Models
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A New Over-Sampling Approach: Random-SMOTE for Learning from Imbalanced Data Sets
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Generative Adversarial Nets
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A Novel Mixed Sampling Algorithm for Imbalanced Data Based on XGBoost
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Imbalanced classification of mental workload using a cost-sensitive majority weighted minority oversampling strategy
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Imbalanced data preprocessing techniques for machine learning: a systematic mapping study
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Toward Design of an Intelligent Cyber Attack Detection System using Hybrid Feature Reduced Approach for IoT Networks
inferredcites →https://doi.org/10.1016/j.chemolab.2023.104933openalex-extracted
An evaluation strategy to select and discard sampling preprocessing methods for imbalanced datasets: A focus on classification models
inferredcites →https://doi.org/10.1016/j.comcom.2020.01.016openalex-extracted
Deep learning and big data technologies for IoT security
inferredcites →https://doi.org/10.1016/j.comcom.2022.07.034openalex-extracted
A dynamic ensemble algorithm for anomaly detection in IoT imbalanced data streams
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Enhancing IoT anomaly detection performance for federated learning
inferredcites →https://doi.org/10.1016/j.ins.2019.11.004openalex-extracted
Data imbalance in classification: Experimental evaluation
inferredcites →https://doi.org/10.1016/j.iot.2019.100059openalex-extracted
Attack and anomaly detection in IoT sensors in IoT sites using machine learning approaches
inferredcites →https://doi.org/10.1016/j.iot.2019.100085openalex-extracted
A smart IoT based system for monitoring and controlling the sub-station equipment
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A Comprehensive Survey on Attacks, Security Issues and Blockchain Solutions for IoT and IIoT
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Machine learning based solutions for security of Internet of Things (IoT): A survey
inferredcites →https://doi.org/10.1016/j.procs.2020.04.257openalex-extracted
Building a Intrusion Detection System for IoT Environment using Machine Learning Techniques
inferredcites →https://doi.org/10.1080/02522667.2020.1799515openalex-extracted
An ensemble hyper-tuned model for IoT sensors attacks and anomaly detection
inferredcites →https://doi.org/10.1109/access.2019.2912631openalex-extracted
Concept Drift Detection and Adaption in Big Imbalance Industrial IoT Data Using an Ensemble Learning Method of Offline Classifiers
inferredcites →https://doi.org/10.1109/access.2019.2944689openalex-extracted
A GAN-Based Anomaly Detection Approach for Imbalanced Industrial Time Series
inferredcites →https://doi.org/10.1109/access.2019.2955086openalex-extracted
Grouped SMOTE With Noise Filtering Mechanism for Classifying Imbalanced Data
inferredcites →https://doi.org/10.1109/access.2020.2994079openalex-extracted
A Novel Attack Detection Scheme for the Industrial Internet of Things Using a Lightweight Random Neural Network
inferredcites →https://doi.org/10.1109/access.2020.3037359openalex-extracted
A Survey of Security Challenges, Attacks Taxonomy and Advanced Countermeasures in the Internet of Things
inferredcites →https://doi.org/10.1109/access.2020.3047838openalex-extracted
Learning With Imbalanced Data in Smart Manufacturing: A Comparative Analysis
inferredcites →https://doi.org/10.1109/access.2021.3073785openalex-extracted
Anomaly Detection in IoT Networks: From Architectures to Machine Learning Transparency
inferredcites →https://doi.org/10.1109/access.2024.3357091openalex-extracted
Hybrid Undersampling and Oversampling for Handling Imbalanced Credit Card Data
inferredcites →https://doi.org/10.1109/bigdataservice52369.2021.00023openalex-extracted
Mitigating Class Imbalance for IoT Network Intrusion Detection: A Survey
inferredcites →https://doi.org/10.1109/ccwc.2019.8666450openalex-extracted
AD-IoT: Anomaly Detection of IoT Cyberattacks in Smart City Using Machine Learning
inferredcites →https://doi.org/10.1109/comst.2019.2962586openalex-extracted
A Survey on the Internet of Things (IoT) Forensics: Challenges, Approaches, and Open Issues
inferredcites →https://doi.org/10.1109/comst.2020.2988293openalex-extracted
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
inferredcites →https://doi.org/10.1109/csde56538.2022.10089252openalex-extracted
Anomaly Detection in IoT Applications using Deep Learning with Class Balancing
inferredcites →https://doi.org/10.1109/ei250167.2020.9346661openalex-extracted
Power IoT Attack Samples Generation and Detection Using Generative Adversarial Networks
inferredcites →https://doi.org/10.1109/globconht56829.2023.10087717openalex-extracted
Locational Detection of False Data Injection Attack in Smart Grid Based on Multilabel Machine Learning Classification Methods
inferredcites →https://doi.org/10.1109/i-pact52855.2021.9696569openalex-extracted
SVM Based DDoS Attack Detection in IoT Using Iot-23 Botnet Dataset
inferredcites →https://doi.org/10.1109/icabcd49160.2020.9183842openalex-extracted
Anomaly Detection on IoT Network Intrusion Using Machine Learning
inferredcites →https://doi.org/10.1109/iccmc48092.2020.iccmc-00023openalex-extracted
Survey on Anomaly Detection of (IoT)- Internet of Things Cyberattacks Using Machine Learning
inferredcites →https://doi.org/10.1109/iceccme52200.2021.9591062openalex-extracted
Denial of Service: A Growing Underrated Threat
inferredcites →https://doi.org/10.1109/iceeccot52851.2021.9708011openalex-extracted
Targeting class imbalance problem using GAN
inferredcites →https://doi.org/10.1109/icic53490.2021openalex-extracted
2021 International Conference on Innovative Computing (ICIC)
inferredcites →https://doi.org/10.1109/icirca54612.2022.9985703openalex-extracted
Analysis of Machine Learning Model for Anomaly and Attack Detection in IoT Devices
inferredcites →https://doi.org/10.1109/jiot.2023.3244810openalex-extracted
Attack Classification of Imbalanced Intrusion Data for IoT Network Using Ensemble-Learning-Based Deep Neural Network
inferredcites →https://doi.org/10.1109/msn50589.2020.00045openalex-extracted
Enhancing IoT Anomaly Detection Performance for Federated Learning
inferredcites →https://doi.org/10.1109/ojies.2022.3152725openalex-extracted
A Fuzzy Logic Recommendation System to Support the Design of Cloud-Edge Data Analysis in Cyber-Physical Systems
inferredcites →https://doi.org/10.1109/ojies.2022.3172899openalex-extracted
SA1D-CNN: A Separable and Attention Based Lightweight Sensor Fault Diagnosis Method for Solar Insecticidal Lamp Internet of Things
inferredcites →https://doi.org/10.1109/uyms54260.2021.9659758openalex-extracted
Comparison of Sampling Methods Using Machine Learning and Deep Learning Algorithms with an Imbalanced Data Set for the Prevention of Violence Against Physicians
inferredcites →https://doi.org/10.1111/exsy.12556openalex-extracted
A machine learning approach for imputation and anomaly detection in IoT environment
inferredcites →https://doi.org/10.1111/exsy.13147openalex-extracted
A hybrid data‐level sampling approach in learning from skewed user‐click data for click fraud detection in online advertising
inferredcites →https://doi.org/10.1111/j.0824-7935.2004.t01-1-00228.xopenalex-extracted
A Multiple Resampling Method for Learning from Imbalanced Data Sets
inferredcites →https://doi.org/10.1142/s0218001409007326openalex-extracted
CLASSIFICATION OF IMBALANCED DATA: A REVIEW
inferredcites →https://doi.org/10.1145/1321440.1321461openalex-extracted
Learning on the border
inferredcites →https://doi.org/10.1145/3343440openalex-extracted
A Systematic Review on Imbalanced Data Challenges in Machine Learning
inferredcites →https://doi.org/10.1177/1550147720916404openalex-extracted
A review on classification of imbalanced data for wireless sensor networks
inferredcites →https://doi.org/10.1186/1687-1499-2013-271openalex-extracted
Intelligent feature selection and classification techniques for intrusion detection in networks: a survey
inferredcites →https://doi.org/10.18280/ria.350102openalex-extracted
Attack and Anomaly Detection in IoT Networks Using Supervised Machine Learning Approaches
inferredcites →https://doi.org/10.3233/ica-2009-0314openalex-extracted
Hybrid sampling for imbalanced data
inferredcites →https://doi.org/10.32604/cmc.2021.018466openalex-extracted
Towards Machine Learning Based Intrusion Detection in IoT Networks
inferredcites →https://doi.org/10.33436/v33i4y202304openalex-extracted
Detecting malicious IoT traffic using Machine Learning techniques
inferredcites →https://doi.org/10.3390/computers12020034openalex-extracted
A Novel Deep Learning-Based Intrusion Detection System for IoT Networks
inferredcites →https://doi.org/10.3390/electronics11091502openalex-extracted
Learning-Based Methods for Cyber Attacks Detection in IoT Systems: A Survey on Methods, Analysis, and Future Prospects
inferredcites →https://doi.org/10.3390/electronics11233854openalex-extracted
Cybersecurity Enhancement of Smart Grid: Attacks, Methods, and Prospects
inferredcites →https://doi.org/10.3390/ijerph17249347openalex-extracted
Cyberattacks Detection in IoT-Based Smart City Applications Using Machine Learning Techniques
inferredcites →https://doi.org/10.3390/s21113726openalex-extracted
A Generative Adversarial Network (GAN) Technique for Internet of Medical Things Data
inferredcites →https://doi.org/10.3390/s21144946openalex-extracted
Analysis of Machine Learning Algorithms for Anomaly Detection on Edge Devices
inferredcites →https://doi.org/10.3390/s22218085openalex-extracted
Anomaly Detection in Industrial IoT Using Distributional Reinforcement Learning and Generative Adversarial Networks
inferredcites →https://doi.org/10.3390/s23020758openalex-extracted
The Effect of Dataset Imbalance on the Performance of SCADA Intrusion Detection Systems
inferredcites →https://doi.org/10.3390/s23052580openalex-extracted
Integrated Probe System for Measuring Soil Carbon Dioxide Concentrations
inferredcites →https://doi.org/10.3390/s23135941openalex-extracted
CICIoT2023: A Real-Time Dataset and Benchmark for Large-Scale Attacks in IoT Environment
inferredcites →https://doi.org/10.47760/ijcsmc.2020.v09i10.012openalex-extracted
Attack and Anomaly Detection in IoT Networks using Machine Learning
inferredcites →https://doi.org/10.48550/arxiv.2206.05840openalex-extracted
GAN based Data Augmentation to Resolve Class Imbalance
inferredcites →https://doi.org/10.5772/7544openalex-extracted
Learning Pattern Classification Tasks with Imbalanced Data Sets
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