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[1]
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TENNER: intrusion detection models for industrial networks based on ensemble learning
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… , Security and Safety,
2024 |
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[2]
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Using ML and DL Algorithms for Intrusion Detection in the Industrial Internet of Things
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AI, Machine Learning …,
2023 |
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[3]
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AI, Machine Learning and Deep Learning: A Security Perspective
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2023 |
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[4]
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Using ML and DL
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… Learning and Deep …,
2023 |
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[5]
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Uma abordagem Ensemble Learning para modelos de detecção de intrusão para redes industriais
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2023 |
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[6]
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A Performance Analysis of Machine Learning Models for Attack Prediction using Different Feature Selection Techniques
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2022 IEEE/ACIS 7th International Conference …,
2022 |
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[7]
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FSAnalysis: a feature selection and analysis mechanism considering balanced and unbalanced bases
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2022 17th Iberian …,
2022 |
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[8]
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Development of a new system to detect denial of service attack using machine learning classification
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Indonesian Journal of …,
2021 |
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[9]
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Building attack detection system base on machine learning
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2021 |
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[10]
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Anomaly Intrusion Detection Using SVM and C4. 5 Classification With an Improved Particle Swarm Optimization (I-PSO)
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2021 |
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[11]
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A Review on Machine Learning Approaches for Network Malicious Behavior Detection in Emerging Technologies
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2021 |
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[12]
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AProposed MODEL FOR DIMENSIONALITY REDUCTION TO IMPROVE THE CLASSIFICATION CAPABILITY OF INTRUSION PROTECTION SYSTEMS
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International Journal of Network Security & Its Applications,
2020 |
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[13]
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A Proposed Model for Dimensionality Reduction to Improve the Classification Capability of Intrusion Protection Systems
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International Journal of Network Security & Its …,
2020 |
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[14]
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An empirical model in intrusion detection systems using principal component analysis and deep learning models
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2020 |
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[15]
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Feature Selection Ranking and Subset-Based Techniques with Different Classifiers for Intrusion Detection
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2019 |
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[16]
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Detecting Anomalous Network Traffic in IoT Networks
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2019 |
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[17]
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Data Model Classification Based on Machine Learning Techniques for Detection of Anomalous Traffic
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Cartagena de Indias,
2019 |
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[18]
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Data Pre-Processing and Classification for Traffic Anomaly Intrusion Detection Using NSLKDD Dataset
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Cybernetics and Information Technologies,
2018 |
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[19]
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A Proposed Machine Learning based Scheme for Intrusion Detection
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2018 |
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[20]
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Intrusion Detection System Using Data Mining
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International Research Journal of Engineering and Technology,
2018 |
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[21]
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A PCA-based method for IoT network traffic anomaly detection
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2018 |
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[22]
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Efficient Techniques for Attack Detection Using Different Features Selection Algorithms and Classifiers
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Wireless Personal Communications,
2018 |
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[23]
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Intrusion detection in RFID system using computational intelligence approach for underground mines
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International Journal of Communication Systems,
2018 |
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[24]
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Designing an online and reliable statistical anomaly detection framework for dealing with large high-speed network traffic.
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2017 |
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[25]
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Addressing Challenges in Big Data Intrusion Detection System using Machine Learning Techniques
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2017 |
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[26]
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Research on Translation and Rotation in Handwritten Digits Recognition
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2017 |
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[27]
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Novel geometric area analysis technique for anomaly detection using trapezoidal area estimation on large-scale networks
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2017 |
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[28]
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Sistema inteligente de apoio à deteção e previsão de cyber ataques em sistemas computacionais
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2017 |
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[29]
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Designing an online and reliable statistical anomaly detection framework for dealing with large high-speed network traffic
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2017 |
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[30]
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Improving intrusion detection using a novel normalization method along with the use of harmony search algorithm for feature selection
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2015 |
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[31]
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Study of stochastic and machine learning techniques for anomalybased web attack detection
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Thesis,
2015 |
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[32]
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Network intrusion detection system using J48 Decision Tree
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Advances in Computing, Communications and Informatics (ICACCI), 2015 International Conference on,
2015 |
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[33]
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Detection and Containment the Attack that Leads to a Denial of Service Attack
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Journal of Algorithms, Computer Network, and Security,
2015 |
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[34]
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Study of stochastic and machine learning tecniques for anomaly-based Web atack detection
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2015 |
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[35]
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Study of stochastic and machine learning techniques for anomaly-based Web attack detection
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2015 |
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[36]
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Feature Based Unsupervised Intrusion Detection
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International Journal of Computer and Information Engineering,
2014 |
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[37]
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L-002 主成分分析を用いた分類器による SQL インジェクション攻撃の自動検出法 (L 分野: ネットワーク?セキュリティ, 一般論文)
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情報科学技術フォーラム講演論文集,
2013 |
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[38]
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基于流的大规模网络安全态势感知关键技术研究
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2013 |
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[39]
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L-002 主成分分析を用いた分類器による SQL インジェクション攻撃の自動検出法 (L 分野: ネットワーク・セキュリティ, 一般論文)
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2013 |
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[40]
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Intrusion Detection System Using Data Mining Technique: Support Vector Machine
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International Journal of Emerging Technology and Advanced Engineering,
2013 |
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[41]
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Intrusion Detection System Based on K-Star Classifier and Feature Set Reduction
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International Organization of Scientific Research Journal of Computer Engineering (IOSR-JCE),
2013 |
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[42]
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Network backbone anomaly detection using double random forests based on non-extensive entropy feature extraction
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Natural Computation (ICNC), 2013 Ninth International Conference on. IEEE,
2013 |
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[43]
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IDS in Telecommunication Network Using PCA
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arXiv preprint arXiv:1308.2779,
2013 |
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[44]
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基于改进非广延熵特征提取的双随机森林实时入侵检测方法
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计算机科学,
2013 |
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[45]
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主成分分析を用いた分類器による SQL インジェクション攻撃の自動検出法
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園田道夫, 松田健, 小泉大城, and 趙晋輝,
2013 |
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[46]
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Improving performance of support vector machine for intrusion detection using discretization
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2013 |
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