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  1. 1
    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems

    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

    Published 2022
    “…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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  2. 2
    Performances of machine learning algorithms for binary classification of network anomaly detection system

    Performances of machine learning algorithms for binary classification of network anomaly detection system by Nawir, M., Amir, A., Lynn, O.B., Yaakob, N., Ahmad, R.B.

    Published 2018
    “…Several issues regarding these available labelled network datasets are discussed in this paper. The aim of this paper to build a network anomaly detection system using machine learning algorithms that are efficient, effective and fast processing. …”
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  3. 3
    A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network

    A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Abdullah F., Ahmad W.S.H.M.W.

    Published 2024
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  4. 4
    Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions

    Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

    Published 2024
    Subjects: “…machine learning algorithms…”
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  5. 5
    Anomaly detection in network traffic using machine learning

    Anomaly detection in network traffic using machine learning by Amir Muhammad Hafiz, Othman, Mohd Faizal, Ab Razak, Mohd Izham, Mohd Jaya, Nurul Azma, Abdullah, Alanda, Alde

    Published 2026
    “…These findings demonstrate that machine learning techniques have strong potential to enhance network security by improving anomaly detection, providing a promising direction for developing intelligent, adaptive intrusion detection.…”
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  6. 6
    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques

    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

    Published 2011
    “…In machine learning algorithm, choosing the most relevant features for each attack is a very important requirement, especially in mobile ad hoc networks where the network topology dynamically changes. …”
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  7. 7
    Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin

    Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

    Published 2022
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  8. 8
    Intruder detection in camera networks using the one-class neighbor machine

    Intruder detection in camera networks using the one-class neighbor machine by Ahmed, Tarem Ozair, Wei, Xianglin, Ahmed, Supriyo, Pathan, Al-Sakib Khan

    Published 2011
    “…We propose a new algorithm based on machine learning techniques for automatic intruder detection in surveillance networks. …”
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  9. 9
    Early detection of dengue disease using extreme learning machine

    Early detection of dengue disease using extreme learning machine by Suhaeri, Suhaeri, Mohd Nawi, Nazri, Fathurahman, Muhamad

    Published 2018
    “…The availability of nowadays clinical data of Dengue disease can be used to train machine learning algorithm in order to automaticaly detect the present of Dengue disease of the patients. …”
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  10. 10
    Anomaly behavior detection using flexible packet filtering and support vector machine algorithms

    Anomaly behavior detection using flexible packet filtering and support vector machine algorithms by Abdul Wahid, Mohammed N.

    Published 2016
    “…FPF of SVM have merged the analyzed results of flexible packet filtering with support vector machine algorithm to get better classification of the captured network traffics and to detect anomalies. …”
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  11. 11
    Detection and classification of conflict flows in SDN using machine learning algorithms

    Detection and classification of conflict flows in SDN using machine learning algorithms by Mutaz Hamed Hussien Khairi, Sharifah Hafizah Syed Ariffin, Nurul Mu'azzah Abdul Latiff, Kamaludin Mohamad Yusof, Mohamed Khalafalla Hassan, Fahad Taha Al-Dhief, Mosab Hamda, Suleman Khan, Muzaffar Hamzah

    Published 2021
    “…As a result, this paper presents several machine learning algorithms that include Decision Tree (DT), Support Vector Machine (SVM), Extremely Fast Decision Tree (EFDT) and Hybrid (DT-SVM) for detecting and classifying conflicting flows in SDNs. …”
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  12. 12
    Earthquake multi-classification detection based velocity and displacement data filtering using machine learning algorithms

    Earthquake multi-classification detection based velocity and displacement data filtering using machine learning algorithms by Murti M.A., Junior R., Ahmed A.N., Elshafie A.

    Published 2023
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  13. 13
    Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.]

    Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.] by Mohd Fuzi, Mohd Faris, Mohd Shahirudin, Syamir, Abd Halim, Iman Hazwam, Jamaluddin, Muhammad Nabil Fikri

    Published 2023
    “…Then, the percentage of detection accuracy was used to compare the detection performance of all five algorithms. …”
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  14. 14
    Attacks detection in 6G wireless networks using machine learning

    Attacks detection in 6G wireless networks using machine learning by Saeed, Mamoon M., Saeed, Rashid A., Gaid, Abdulguddoos S. A., Mokhtar, Rania A., Khalifa, Othman Omran, Ahmed, Zeinab E.

    Published 2023
    “…The Attacks Detection in 6G (AD6Gs) wireless networks created by this research uses a Machine Learning (ML) algorithm. …”
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  15. 15
    Anomaly detection in ICS datasets with machine learning algorithms

    Anomaly detection in ICS datasets with machine learning algorithms by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Abdul Rahman, Farah Diyana, Tahir, Mohammad

    Published 2021
    “…The activity traffic between ICS components is analyzed and packet inspection of the dataset is performed for the ICS network. The features of flow-based network traffic are extracted for behavior analysis with port-wise profiling based on the data baseline, and anomaly detection classification and prediction using machine learning algorithms are performed.…”
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  16. 16
    Phishing attack detection using machine learning method

    Phishing attack detection using machine learning method by Jupin, John Arthur

    Published 2019
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  17. 17
    A hybrid intrusion detection system based on different machine learning algorithms

    A hybrid intrusion detection system based on different machine learning algorithms by Atefi, Kayvan, Yahya, Saadiah, Dak, Ahmad Yusri, Atefi, Arash

    Published 2013
    “…There are numerous study in intrusion detection system (IDS) especially with Genetic algorithms (GA) and Support Vector Machine (SVM) but most of them did not get the potential of hybrid SVM using GA. …”
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  18. 18
    Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm

    Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

    Published 2021
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  19. 19
    FAULT DETECTION AND DIAGNOSIS ALGORITHMS USING NARX NEURAL NETWORK AND SUPPORT VECTOR MACHINE

    FAULT DETECTION AND DIAGNOSIS ALGORITHMS USING NARX NEURAL NETWORK AND SUPPORT VECTOR MACHINE by TAQVI, SYED ALI AMMAR

    Published 2020
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  20. 20
    Malware Classification and Detection using Variations of Machine Learning Algorithm Models

    Malware Classification and Detection using Variations of Machine Learning Algorithm Models by Andi Maslan, Andi Maslan, Abdul Hamid, Abdul Hamid

    Published 2025
    “…The purpose of the study is to detect, classify malware attacks using a variety of ML Algorithm models such as SVM, KNN and Neural Network and testing detection performance. …”
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