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  1. 1

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…Thus, this study proposes the development of algorithms to detect and classify jamming attacks using a set of parameters on the physical layer and MAC in MANET. …”
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    Thesis
  2. 2

    Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin by Mohd Nordin, Ahmad Nasreen Aqmal

    Published 2024
    “…The project successfully achieves its predetermined objectives, culminating in the development of an effective Remote to Local (R2L) Intrusion Detection System utilizing the Decision Tree algorithm. …”
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    Thesis
  3. 3

    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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    Thesis
  4. 4

    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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    Article
  5. 5

    Campus hybrid intrusion detection system using SNORT and C4.5 Algorithm by Slamet, ., Izzeldin, I. Mohd, Fahmi, Samsuri

    Published 2020
    “…As a result of implementing this system: misused detection module uses the signature of attacks to detection the known attacks; anomaly detection module can detect the unknown attacks; signature generation module extracts the signature of attacks that are detected by Anomaly Detection System module, and maps the signatures into snort rules.…”
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    Conference or Workshop Item
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    Machine learning algorithms in context of intrusion detection by Mehmood, T., Rais, H.B.Md.

    Published 2016
    “…Many machine learning techniques have been developed to cope with this problem. These machine learning algorithms develop a detection model in a training phase. …”
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    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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    Article
  9. 9

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

    Published 2022
    “…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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    Article
  10. 10

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

    Published 2022
    “…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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    Article
  11. 11

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

    Published 2022
    “…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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    Article
  12. 12

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

    Published 2023
    “…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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    Article
  13. 13

    Using streaming data algorithm for intrusion detection on the vehicular controller area network by Sharmin, Shaila, Mansor, Hafizah, Abdul Kadir, Andi Fitriah, Abdul Aziz, Normaziah

    Published 2022
    “…The Controller Area Network (CAN), which is a protocol for the in-vehicle network, is lacking in security features, making the CAN bus vulnerable to a range of cyberattacks such as message injections, replay attacks, and denial of service attacks. This has prompted researchers to develop statistical and machine learning based intrusion detection systems for the CAN bus that use various features such as message timing and frequency to detect attacks. …”
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    Proceeding Paper
  14. 14

    Secure address resolution protocol proxy in software defined network by Munther, Munther Numan

    Published 2018
    “…In addition, ARP based attack detection technique combines ARP storm and ARP spoofing detection algorithms. …”
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    Thesis
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    Mitigating Slow Hypertext Transfer Protocol Distributed Denial of Service Attacks in Software Defined Networks by Akanji, Oluwatobi Shadrach, Abisoye, Opeyemi Aderiike, Iliyasu, Mohammed Awwal

    Published 2021
    “…This study contributes to the ongoing research in detecting and mitigating slow HTTP DDoS attacks with emphasis on the use of machine learning classification and meta-heuristic algorithms.…”
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    Article
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    Remote to Local Attack Detection Using Supervised Neural Network by Iftikhar, Ahmad, Azween, Abdullah, Abdullah , S. Alghamdi

    Published 2010
    “…This technique uses sampled dataset from Kddcup99 that is standard for benchmarking of attack detection tools. The backpropagation algorithm is used for training the feedforward neural network. …”
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    Conference or Workshop Item
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    Detection of black hole attacks in mobile ad hoc networks via HSA-CBDS method by Fahad, Ahmed Mohammed, Ahmed, Abdulghani Ali, Alghushami, Abdullah H., Alani, Sammer

    Published 2019
    “…Therefore, this authentication process must be further investigated to develop efficient security techniques. This paper proposes a solution for detecting black hole attacks on MANET by using harmony search algorithm (DBHSA), which uses harmony search algorithm (HSA) to mitigate the lateness problem caused by cooperative bait detection scheme (CBDS). …”
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    Book Chapter
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