Search Results - (( attack detection learning algorithm ) OR ( parallel optimization method algorithm ))

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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
    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System

    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

    Published 2019
    “…As network attackers keep changing their methods of attack execution to evade the deployed intrusion-detection systems (IDS), machine learning (ML) algorithms have been introduced to boost the performance of the IDS. …”
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  3. 3
    An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm

    An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm by Abdulkareem, Fatimah Saleem, Mohd Sani, Nor Fazlida

    Published 2023
    “…To achieve this, we measured the performance of three deep learning algorithms for normal and abnormal detection of IDS, and a comparison was made to select the best performance of the deep learning algorithm for detection in IDS, such as RNN, DBN and CNN. …”
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  4. 4
    A comparative study between deep learning algorithm and bayesian network on Advanced Persistent Threat (APT) attack detection

    A comparative study between deep learning algorithm and bayesian network on Advanced Persistent Threat (APT) attack detection by Ooi, Hui Ni, Ab Rahman, Nurul Hidayah

    Published 2021
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  5. 5
    Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system

    Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system by Maseer, Ziadoon Kamil

    Published 2022
    “…In future, the HW-DBN algorithm can be proposed as an integrated deep Learning for the classification performance of attack detection models.…”
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  6. 6
    A comparative study between deep learning algorithm and bayesian network on Advanced Persistent Threat (APT) attack detection

    A comparative study between deep learning algorithm and bayesian network on Advanced Persistent Threat (APT) attack detection by Ooi, Hui Ni, Ab Rahman, Nurul Hidayah

    Published 2021
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  7. 7
    Phishing attack detection using machine learning method

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

    Published 2019
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  8. 8
    Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband

    Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband by Shamshirband, Shahaboddin

    Published 2014
    “…We investigate the detection capability based on the fuzzy Q-learning (FQL) algorithm and evaluate it using distribute denial of service attacks (DDoS). …”
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  9. 9
    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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  10. 10
    An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack

    An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack by Yusof, Ahmad Riza’ain, Udzir, Nur Izura, Selamat, Ali

    Published 2016
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  11. 11
    Designing a new model for Trojan horse detection using sequential minimal optimization

    Designing a new model for Trojan horse detection using sequential minimal optimization by Madihah Mohd Saudi, Abuzaid A.M., Taib B.M., Abdullah Z.H.

    Published 2024
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  12. 12
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. The present study proposes an efficient DDoS attack detection model. …”
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  13. 13
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A.

    Published 2022
    “…Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. The present study proposes an efficient DDoS attack detection model. …”
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  14. 14
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. The present study proposes an efficient DDoS attack detection model. …”
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  15. 15
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

    Published 2022
    “…Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. The present study proposes an efficient DDoS attack detection model. …”
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  16. 16
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

    Published 2023
    “…Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. The present study proposes an efficient DDoS attack detection model. …”
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  17. 17
    Machine learning algorithms in context of intrusion detection

    Machine learning algorithms in context of intrusion detection by Mehmood, T., Rais, H.B.Md.

    Published 2016
    “…These machine learning algorithms develop a detection model in a training phase. …”
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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
    “…IP-PBX face challenges in detecting and mitigating malicious traffic. In this research, Support Vector Machine (SVM) machine learning detection & prevention algorithm were developed to detect this type of attacks Two other techniques were benchmarked decision tree and Naïve Bayes. …”
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  19. 19
    Detection of DDoS attacks in IoT networks using machine learning algorithms

    Detection of DDoS attacks in IoT networks using machine learning algorithms by Abdulrahman Alwan, Alwan Ahmed, Shah, Asadullah, Abdulrahman Alwan, Alwan Abdullah, Laghari, Shams Ul Arfeen

    Published 2025
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  20. 20
    DeepIoT.IDS: Hybrid deep learning for enhancing IoT network intrusion detection

    DeepIoT.IDS: Hybrid deep learning for enhancing IoT network intrusion detection by A. Mostafa, Salama, Al-Azzawi, Ziadoon Kamil Maseer, Bahaman, Nazrulazhar, Yusof, Robiah, Musa, Omar, Al-rimy, Bander Ali Saleh

    Published 2021
    “…Recently, researchers have suggested deep learning (DL) algorithms to define intrusion features through training empirical data and learning anomaly patterns of attacks. …”
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