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  1. 1
    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 the past decades, machine learning methods have been successfully used in several intrusion detection methods because of their ability to discover and detect novel attacks. …”
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  2. 2
    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 Mohammad Azmi Ridwan, Dr.

    Published 2023
    “…The dataset development for both algorithms is carried out via simulations in Graphical Network Simulator 3 (GNS3). …”
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  3. 3
    Modelling of intelligent intrusion detection system: making a case for snort

    Modelling of intelligent intrusion detection system: making a case for snort by Olanrewaju, Rashidah Funke, Ku zahir, Ku Nor Afiza, Asnawi, Ani Liza, Sanni, Mistura Laide, Ahmed, Abdulkadir Adekunle

    Published 2018
    “…Hence, this study proposes a method for early detection of an intrusion by using Snort software. …”
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    Proceeding Paper
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  4. 4
    Secure and Energy-Efficient Data Aggregation Method Based on an Access Control Model

    Secure and Energy-Efficient Data Aggregation Method Based on an Access Control Model by Jasim, Ahmed Abdulhadi, Idris, Mohd Yamani Idna, Azzuhri, Saaidal Razalli, Issa, Noor Riyadh, Noor, Noorzaily Mohamed, Kakarla, Jagadeesh, Amiri, Iraj Sadegh

    Published 2019
    “…To ensure the reliability of our proposed method, we simulate two well-known attacks, called Sybil and sinkhole attacks. …”
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  5. 5
    A controller-agnostic random oracle based intrusion detection method in software defined networks / Adnan

    A controller-agnostic random oracle based intrusion detection method in software defined networks / Adnan by Adnan, -

    Published 2016
    “…To validate our proposed approach, we also carried simulation using a publicly available benchmark data-set with K-fold cross validation to exhibit the performance of the proposed method. …”
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  6. 6
    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
    “…Therefore, an intrusion detection method for attacking and detecting anomalies in an IoT system must be enhanced. …”
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  7. 7
    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
    “…This means that Multilayer Perceptron algorithm can detect APT attack more accurately. …”
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  8. 8
    Phishing attack detection using machine learning method

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

    Published 2019
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    Undergraduates Project Papers
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  9. 9
    Wormhole attack detection mechanism in mobile ad hoc network using neighborhood information and path tracing algorithm

    Wormhole attack detection mechanism in mobile ad hoc network using neighborhood information and path tracing algorithm by Enshaei, Mehdi

    Published 2015
    “…Path Tracing (PT) Algorithm was proposed to detect and prevent exposed wormhole attacks in MANET. …”
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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
    Early detection and mitigation of DDoS attacks in software defined networks

    Early detection and mitigation of DDoS attacks in software defined networks by Al-Saadi, Mustafa Yahya Zakariya

    Published 2018
    “…To detect and mitigate this attack at its early stages, an entropy-based DDoS attack detection and mitigation algorithm was proposed. …”
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  12. 12
    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
    “…This means that Multilayer Perceptron algorithm can detect APT attack more accurately. …”
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  13. 13
    Incremental learning for large-scale stream data and its application to cybersecurity

    Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

    Published 2015
    “…Using this method, the learning time is shorten, and thus, the DDoS backscatter can be detected fast. …”
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  14. 14
    An Enhanced Mechanism To Detect Drdos Attacks On Dns Using Adaptive Thresholding Technique

    An Enhanced Mechanism To Detect Drdos Attacks On Dns Using Adaptive Thresholding Technique by Al Ogaili, Riyadh Rahef Nuiaa

    Published 2023
    “…Thus, this thesis presents a mechanism for detecting DRDoS attacks on DNS that is strengthened by the use of modified metaheuristic algorithms and adaptive thresholding techniques based on machine learning algorithms (EMDDMAT).…”
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  15. 15
    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
    “…While the effectiveness of some machine learning algorithms in detecting certain types of network intrusion has been ascertained, the situation remains that no single method currently exists that can achieve consistent results when employed for the detection of multiple attack types. …”
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  16. 16
    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak

    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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  17. 17
    A comparative analysis of metaheuristic algorithms in fuzzy modelling for phishing attack detection

    A comparative analysis of metaheuristic algorithms in fuzzy modelling for phishing attack detection by Noor Syahirah, Nordin, Mohd Arfian, Ismail, Tole, Sutikno, Shahreen, Kasim, Rohayanti, Hassan, Zalmiyah, Zakaria, Mohd Saberi, Mohamad

    Published 2021
    “…The increasing and never-ending case of phishing attack has led to more automated approaches in detecting phishing attack. …”
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  18. 18
    An improved method using fuzzy system based on hybrid boahs for phishing attack detection

    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
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  19. 19
    An efficient trust-based decision-making approach for WSNs: Machine learning oriented approach

    An efficient trust-based decision-making approach for WSNs: Machine learning oriented approach by Khan, T., Singh, K., Shariq, M., Ahmad, K., Savita, K.S., Ahmadian, A., Salahshour, S., Conti, M.

    Published 2023
    “…Simulation experiments exhibit the effectiveness of the proposed trust evaluation method in terms of change in trust values, malicious nodes detection (94), FNR (0.9), F1-Score (0.6), and accuracy (92) in the presence of 50 malicious nodes. …”
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  20. 20
    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
    “…Asymmetrically, anomaly based detection method can detect novel attacks but it has high false positive rate. …”
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