[1]
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A Rule-Based Approach for Grey Hole Attack Prediction in Wireless Sensor Networks.
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Intelligent Automation & Soft …,
2023 |
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[2]
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Big Data Analytics and Machine Learning
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Data Analytics …,
2022 |
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[3]
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Customer Lifetime Value Analysis Based on Machine Learning
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Proceedings of the 6th International Conference on …,
2022 |
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[4]
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Empirical Analysis of Machine Learning Models towards Adaptive Network Intrusion Detection Systems
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2022 4th International …,
2022 |
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[5]
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Analysis of Network Technologies and Cyber security Assessment for Enhancing Machine Learning, Grid Computing and Cyber-Physical Connectivity Internetwork …
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… in Technology and …,
2022 |
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[6]
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Important Features Selection and Classification of Adult and Child from Handwriting Using Machine Learning Methods
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Applied Sciences,
2022 |
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[7]
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Diabetes prediction using Multilayer Perceptron
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2022 |
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[8]
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Comparison of Machine Learning Algorithms for Anomaly Detection in Train's Real-Time Ethernet using an Intrusion Detection System
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2022 |
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[9]
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Comparison of feature selection algorithms for Data classification problems
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2022 VIII International …,
2022 |
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[10]
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A Survey on Threat Hunting: Approaches and Applications
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2022 7th IEEE International …,
2022 |
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[11]
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Random Forest Permutation Feature Importance for Feature Selection in Ion Mobility Spectrometry
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2022 |
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[12]
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EGD-SNet: A computational search engine for predicting an end-to-end machine learning pipeline for Energy Generation & Demand Forecasting
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Applied Energy,
2022 |
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[13]
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A hybrid machine learning model for intrusion detection in VANET
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Computing,
2022 |
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[14]
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Cervical Cancer Diagnosis Using an Integrated System of Principal Component Analysis, Genetic Algorithm, and Multilayer Perceptron
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Healthcare,
2022 |
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[15]
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Detecting zero-day intrusion attacks using semi-supervised machine learning approaches
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IEEE Access,
2022 |
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[16]
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Selection of breast features for young women in northwestern China based on the random forest algorithm
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Textile Research …,
2022 |
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[17]
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Statistical analysis and prediction of spatial resilient modulus of coarse-grained soils for pavement subbase and base layers using MLR, ANN and Ensemble …
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Innovative Infrastructure Solutions,
2022 |
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[18]
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Feature selection for credit risk classification
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International Conference on Intelligent Systems and …,
2022 |
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[19]
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Bridging the Last-Mile Gap in Network Security via Generating Intrusion-Specific Detection Patterns through Machine Learning
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Security and Communication …,
2022 |
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[20]
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Enhancing Detection of R2L Attacks by Multistage Clustering Based Outlier Detection
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Wireless Personal …,
2022 |
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[21]
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Effective Attribute Selection for Multi-dimensional Root Cause Analysis
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2022 IEEE 33rd …,
2022 |
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[22]
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A feature selection strategy for improving software maintainability prediction
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Intelligent Data Analysis,
2022 |
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[23]
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An Incisive Analysis of Advanced Persistent Threat Detection Using Machine Learning Techniques
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Computational Intelligence in Data …,
2022 |
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[24]
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Low-Latency Intrusion Detection Using a Deep Neural Network
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IT Professional,
2022 |
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[25]
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Sistemas inteligentes baseados em deep-wavelet e redes neurais convolucionais para apoio ao diagnóstico de câncer de mama usando imagens termográficas
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2022 |
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[26]
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Máquina de elementos finitos para seleção de características de anomalias em redes de computadores
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2021 |
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[27]
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Intrusion Detection System Berbasis Seleksi Fitur Dengan Kombinasi Filter Information Gain Ratio Dan Correlation
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Jurnal Teknologi Informasi …,
2021 |
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[28]
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Network Anomaly Detection Technology Based on Deep Learning
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2021 IEEE 3rd …,
2021 |
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[29]
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A new feature selection approach and classification technique for current intrusion detection system
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Okay, R Samet, Ö Aslan - 2021 6th International …,
2021 |
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[30]
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SABADT: hybrid intrusion detection approach for cyber attacks identification in WLAN
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Okay, Ö Aslan, R Eryigit, R Samet - IEEE Access,
2021 |
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[31]
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Feature selection and comparison of classification algorithms for wireless sensor networks
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Journal of Ambient Intelligence and …,
2021 |
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[32]
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MPF-Net: A computational multi-regional solar power forecasting framework
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… and Sustainable Energy …,
2021 |
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[33]
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Signal Anomaly Detection of Bridge SHM System Based on Two-Stage Deep Convolutional Neural Networks
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Structural Engineering …,
2021 |
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[34]
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Analysis of Sales Vitamins Drugs Covid-19 Pandemic with the Random Forest Method
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Jurnal Mantik,
2021 |
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[35]
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Detection of phising websites using machine learning approaches
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… Conference on Data …,
2021 |
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[36]
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The MIGREX study: Prevalence and risk factors of sexual dysfunction among migraine patients
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2021 |
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[37]
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A Powerful Ensemble Learning Approach for Improving Network Intrusion Detection System (NIDS)
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2021 Fifth International …,
2021 |
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[38]
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Quotidian Sales Forecasting using Machine Learning
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… and Smart Electrical …,
2021 |
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[39]
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Benchmarking of machine learning for anomaly based intrusion detection systems in the CICIDS2017 dataset
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2021 |
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[40]
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Large group activity security risk assessment and risk early warning based on random forest algorithm
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2021 |
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[41]
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Predicting DOS-DDOS Attacks: Review and Evaluation Study of Feature Selection Methods based on Wrapper Process
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International Journal of Advanced Computer Science and Applications,
2021 |
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[42]
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Is it possible developing reliable prediction models considering only the pipe's age for decision-making in sewer asset management?
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2021 |
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[43]
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An efficient metaheuristic algorithm based feature selection and recurrent neural network for DoS attack detection in cloud computing environment
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2021 |
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[44]
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Detection System for the Network Data Security with a profound Deep learning approach
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Proceedings of the 6th International Conference on Communication and Electronics Systems,
2021 |
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[45]
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Feature Selection and Analysis in Air Quality Data
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2021 |
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[46]
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A Review of Support Vector Machine-based Intrusion Detection System for Wireless Sensor Network with Different Kernel Functions
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2021 |
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[47]
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A Profound Deep learning approach for Detection System in Network Data
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2021 |
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[48]
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Using Embedded Feature Selection and CNN for Classification on CCD-INID-V1—A New IoT Dataset
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2021 |
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[49]
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A Two Layer Machine Learning System for Intrusion Detection Based on Random Forest and Support Vector Machine
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2020 |
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[50]
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تشخیص نفوذ در شبکه با استفاده از ترکیب شبکههای عصبی مصنوعی بهصورت سلسله مراتبی
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2020 |
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[51]
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Penerapan Analisis Random Forest pada Prototype Sistem Prediksi Harga Kamera Bekas Menggunakan Flask
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2020 |
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[52]
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Sistem Prediksi Harga Sewa Kost dengan Menggunakan Random Forest Analytics (Studi Kasus: Kost Eksklusif di Daerah Istimewa Yogyakarta)
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2020 |
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[53]
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Advances in Modelling and Analysis B
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2020 |
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[54]
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Evaluation of Intrusion Detection System based on Gaussian Mixture and K-Means Clustering with Random Forest Classifier
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2020 |
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[55]
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Network Intrusion Detection using a combination of artificial neural networks in a hierarchical manner
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2020 |
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[56]
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A Partial Approach to Intrusion Detection
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2020 |
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[57]
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Machine Learning and Deep Learning Techniques for Cybersecurity: A Review.
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2020 |
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[58]
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A survey on machine learning techniques for cyber security in the last decade
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2020 |
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[59]
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A Machine Learning Intrusion Prevention And Detection System Using Securing Smart Grid
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2020 |
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[60]
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Ransomware Detection Using Random Forest Technique
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2020 |
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[61]
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A Feature Selection Algorithm for Intrusion Detection System Based on New Meta-Heuristic Optimization
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2020 |
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[62]
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Ensembling Learning for Intrusion Detection
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2020 |
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[63]
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APT datasets and attack modeling for automated detection methods: A review
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2020 |
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[64]
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A Review on Network Intrusion Detection System Using Machine Learning
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2020 |
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[65]
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Failure Prediction Model Using Iterative Feature Selection for Industrial Internet of Things
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2020 |
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[66]
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Predictor selection and attack classification using random forest for intrusion detection
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2020 |
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[67]
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Predicting user posting activities in online health communities with deep learning
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2020 |
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[68]
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Bi-directional Recurrent Neural network for Intrusion Detection System (IDS) in the internet of things (IoT)
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2020 |
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[69]
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A novel dynamic multi-criteria ensemble selection mechanism applied to drinking water quality anomaly detection
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2020 |
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[70]
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Machine Learning and Deep Learning Techniques for Cybersecurity: A Review
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2020 |
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[71]
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An Efficient Mixed Attribute Outlier Detection Method for Identifying Network Intrusions
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2020 |
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[72]
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Dos attack forecasting: A comparative study on wrapper feature selection
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2020 |
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[73]
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Performance Analysis of Machine Learning Techniques Used in Intrusion Detection Systems
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2020 |
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[74]
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A Heuristic Approach for Intrusion Detection in IoT Environment
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2020 |
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[75]
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A Review on Machine Learning and Deep Learning Perspectives of IDS for IoT: Recent Updates, Security Issues, and Challenges
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2020 |
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[76]
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Investigating and Suggesting the Evaluation Dataset for Image Classification Model
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2020 |
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[77]
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Data mining for systems medicine and spectroscopic profiling: methods and applications
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2020 |
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[78]
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On evaluation of network intrusion detection systems: Statistical analysis of CIDDS-001 dataset using machine learning techniques
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2019 |
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[79]
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Autocalibration of Outlier Threshold with Autoencoder Mean Probability Score
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2019 |
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[80]
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COSMOS: Collaborative, Seamless and Adaptive Sentinel for the Internet of Things
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2019 |
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[81]
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Integrated analysis of the miRNA–mRNA next-generation sequencing data for finding their associations in different cancer types
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2019 |
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[82]
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A Deep Learning Approach for Network Intrusion Detection Based on NSL-KDD Dataset
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2019 |
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[83]
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Ensembles for feature selection: A review and future trends
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2019 |
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[84]
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Analysis of NSL KDD Dataset Using Classification Algorithms for Intrusion Detection System
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2019 |
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[85]
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Ensemble-based semi-supervised learning approach for a distributed intrusion detection system
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2019 |
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[86]
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Random forest based optimal feature selection for partial discharge pattern recognition in HV cables
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2019 |
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[87]
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Wireless Sensor Networks Intrusion Detection Based on SMOTE and the Random Forest Algorithm
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2019 |
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[88]
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MODEL FOR IMPROVING PERFORMANCE OF NETWORK INTRUSION DETECTION BASED ON MACHINE LEARNING TECHNIQUES
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2019 |
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[89]
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Investigasi log jaringan untuk deteksi serangan Distributed Denial Of Service (DDOS) dengan menggunakan metode general REGRESSION neural network
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2019 |
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[90]
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A Machine Learning-Based Lightweight Intrusion Detection System for the Internet of Things
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Revue d'Intelligence Artificielle,
2019 |
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[91]
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Hybrid Architecture for Distributed Intrusion Detection System.
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2019 |
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[92]
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Hybrid Architecture for Distributed Intrusion Detection System
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Ingénierie des Systèmes d’Information (ISI),
2019 |
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[93]
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A Novel Algorithm for Human Activity Determination Feature Selection and Classification
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2019 |
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[94]
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Hybrid Feature Selection Method Based on a Naïve Bayes Algorithm that Enhances the Learning Speed while Maintaining a Similar Error Rate in Cyber ISR
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2018 |
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[95]
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An Unsupervised Approach for Selection of Candidate Feature Set Using Filter Based Techniques.
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2018 |
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[96]
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An Integrated Perceptron Kernel Classifier for Intrusion Detection System.
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2018 |
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[97]
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Hybrid Feature Selection Method Based on a Naïve Bayes Algorithm that Enhances the Learning Speed while Maintaining a Similar Error Rate in Cyber ISR.
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2018 |
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[98]
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Accurate Diabetes Risk Stratification Using Machine Learning: Role of Missing Value and Outliers
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Journal of Medical Systems,
2018 |
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[99]
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Analysis of Feature Selection and Ensemble Classifier Methods for Intrusion Detection
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International Journal of Natural Computing Research (IJNCR),
2018 |
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[100]
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Feature-Selection-Based Ransomware Detection with Machine Learning of Data Analysis
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2018 |
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[101]
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Recurrent Neural Network Architectures Toward Intrusion Detection
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2018 |
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[102]
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An Unsupervised Approach For Selection of Candidate Feature Set Using Filter Based Techniques
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Gazi University Journal of Science,
2018 |
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[103]
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Comparison of Recurrent Neural Network Algorithms for Intrusion Detection Based on Predicting Packet Sequences
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2018 |
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[104]
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An Integrated Perceptron Kernel Classifier for Intrusion Detection System
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2018 |
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[105]
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Survey on SDN based network intrusion detection system using machine learning approaches
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Peer-to-Peer Networking and Applications,
2018 |
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[106]
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Recent Advances in Ensembles for Feature Selection
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Recent Advances in Ensembles for Feature Selection,
2018 |
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[107]
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Random Forest Algorithm in Intrusion Detection System: A Survey
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2018 |
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[108]
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Automatic Intrusion Detection System Using Deep Recurrent Neural Network Paradigm
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2018 |
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[109]
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Emerging Challenges
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Recent Advances in Ensembles for Feature Selection,
2018 |
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[110]
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Network Data Security for the Detection System in the Internet of Things with Deep Learning Approach
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International Journal of Advanced Engineering Research and Science,
2018 |
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[111]
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On Evaluation of Network Intrusion Detection Systems: Statistical Analysis of CIDDS-001 Dataset Using Machine Learning Techniques.
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2018 |
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[112]
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An Efficient Feature Selection Approach for Network-based Intrusion Detection System Using Machine Learning Algorithm
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2018 |
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[113]
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Implementasi Data Mining dengan Seleksi Fitur untuk Klasifikasi Serangan pada Intrusion Detection System (IDS)
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2017 |
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[114]
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A Hybrid Feature Selection Framework for Enhancing Network Intrusion Detection
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2017 |
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[115]
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A feature selection algorithm for IDS
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2017 |
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[116]
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A Hybrid Feature Selection Method for Improved Detection of Wired/Wireless Network Intrusions
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Wireless Personal Communications,
2017 |
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[117]
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基於資料探勘技術應用於網路異常偵測
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國立臺北教育大學學位論文,
2017 |
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[118]
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Modelling Spatial Behaviour in Music Festivals Using Mobile Generated Data and Machine Learning
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2017 |
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[119]
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Deep Learning Approach for Intrusion Detection System (IDS) in the Internet of Things (IoT) Network using Gated Recurrent Neural Networks (GRU)
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Dissertation, Wright State University,
2017 |
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[120]
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A Review on Cyber Security Datasets for Machine Learning Algorithms
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2017 |
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[121]
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DV-iSucLys: Decision Voting to Improve Protein Lysine Succinylation Site Identification from Sequence Data
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2017 |
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[122]
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Contribution des techniques de datamining dans l'amélioration des systèmes de détection d'intrusion dans les réseaux informatiques
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2017 |
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[123]
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IMPLEMENTASI DATA MINING DENGAN SELEKSI FITUR UNTUK KLASIFIKASI SERANGAN INTRUSION DETECTION SYSTEM (IDS)
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2017 |
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[124]
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Siber Saldırılar için Rastgele Orman Algoritması Kullanılarak Öznitelik Seçimi
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[125]
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Hybrid Architecture for Distributed Intrusion Detection System Using Semi-supervised Classifiers in Ensemble Approach Hybrid Architecture for Distributed …
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SR Khonde
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[126]
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A Machine Learning-Based Lightweight Intrusion Detection System for the Internet of Things A Machine Learning-Based Lightweight Intrusion Detection …
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S Fenanir, F Semchedine
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[127]
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Light Gradient Boosting with Hyper Parameter Tuning Optimization for COVID-19 Prediction
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[128]
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Network Intrusion Detection System Using KNN and Naive Bayes Classifiers
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