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  1. 1
    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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  2. 2
    The optimization of stepping stone detection: packet capturing steps

    The optimization of stepping stone detection: packet capturing steps by Omar, Mohd. Nizam, Maarof, Mond. Aizaini, Zainal, Anazida

    Published 2006
    “…This paper proposes an optimized packet capturing stone detection algorithm that can shorten the response time of overall response mechanism. …”
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  3. 3
    QoS evaluation of different TCPs congestion control algorithm using NS2

    QoS evaluation of different TCPs congestion control algorithm using NS2 by Tarmizi, M., Albagul, A., Khalifa, Othman Omran, Wahyudi, Martono

    Published 2006
    “…To achieve this, the users implement a flow control algorithm that controls the rate at which data packets are sent into the Internet. …”
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  4. 4
    The optimization of stepping stone detection : packet capturing steps

    The optimization of stepping stone detection : packet capturing steps by Omar, Mohd. Nizam, Maarof, Mohd. Aizaini, Zainal, Anazida

    Published 2006
    “…This paper proposes an optimized packet capturing stone detection algorithm that can shorten the response time of overall response mechanism. …”
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  5. 5
    The optimization of stepping stone detection: Packet capturing steps

    The optimization of stepping stone detection: Packet capturing steps by Omar, Mohd Nizam, Maarof, Mohd Aizaini, Zainal, Anazida

    Published 2006
    “…This paper proposes an optimized packet capturing stone detection algorithm that can shorten the response time of overall response mechanism.The aim of the research is to improve the packet capturing step in stepping stone algorithm, thus, improve the response from overall detection and response system.The proposed method is to use small size of user buffer and kernel buffer.Experiments were conducted with two types of packet stream; i) 10 kbps and ii) 10 000 kbps data generated by Tfgen (packet generator) tools and nine combinations of different buffer sizes for each network packet stream were tested.Results from the experiment were analyzed. …”
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  6. 6
    Multiuser Sensing for Opportunistic Spectrum Access in Cognitive Radio Networks

    Multiuser Sensing for Opportunistic Spectrum Access in Cognitive Radio Networks by Armi, Nasrullah, Yusoff, Mohd Zuki, M Saad, M Naufal

    Published 2011
    “…CR users perform spectrum sensing and detect primary users (PUs) signal even when they are transmitting data packet. …”
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  7. 7
    Multiuser Sensing for Opportunistic Spectrum Access in Cognitive Radio Networks

    Multiuser Sensing for Opportunistic Spectrum Access in Cognitive Radio Networks by Armi, Nasrullah, Yusoff, Mohd Zuki, M Saad, M Naufal

    Published 2011
    “…CR users perform spectrum sensing and detect primary users (PUs) signal even when they are transmitting data packet. …”
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  8. 8
    Features selection for IDS in encrypted traffic using genetic algorithm

    Features selection for IDS in encrypted traffic using genetic algorithm by Barati, Mehdi, Abdullah, Azizol, Mahmod, Ramlan, Mustapha, Norwati, Udzir, Nur Izura

    Published 2013
    “…Intrusion Detection System (IDS) is one method to detect unauthorized intrusions into computer systems and networks. …”
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  9. 9
    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices

    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2013
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  10. 10
    Performance evaluation of real-time multiprocessor scheduling algorithms

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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  11. 11
    Effects of Authentication of Users in Mobile Internet Protocol Version 6

    Effects of Authentication of Users in Mobile Internet Protocol Version 6 by Obenofunde, Simon Tabi

    Published 2004
    “…Presently, mobility is difficult, if not impossible to detect at the application layer though easily detectable at the network layer. …”
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  12. 12
    Features selection for ids in encrypted traffic using genetic algorithm

    Features selection for ids in encrypted traffic using genetic algorithm by Barati, Mehdi, Abdullah, Azizol, Mahmod, Ramlan, Mustapha, Norwati, Udzir, Nur Izura

    Published 2013
    “…This paper presents a hybrid feature selection using Genetic Algorithm and Bayesian Network to improve Brute Force attack detection in Secure Shell (SSH) traffic. …”
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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
    “…Usually, it is hard to detect DDoS backscatter from the unlabeled packets, where an expert is needed to analyze every packet manually. …”
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  14. 14
    Precise ICMP Traceback Based On Normal Flow Filtration in Denial of Services Attack

    Precise ICMP Traceback Based On Normal Flow Filtration in Denial of Services Attack by Izaddoost, Alireza

    Published 2008
    “…In other words, it is unable to differentiate legitimate user and attacker, when both of them sending packet via same route to the victim. …”
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  15. 15
    Route Optimization System

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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  16. 16
    Machine Learning Based Two Phase Detection and Mitigation Authentication Scheme for Denial-of-Service Attacks in Software Defined Networks

    Machine Learning Based Two Phase Detection and Mitigation Authentication Scheme for Denial-of-Service Attacks in Software Defined Networks by Najmun, Najmun

    Published 2024
    “…This scheme incorporates machine learning techniques by utilizing Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) classification algorithms to accurately identify and handle malicious network traffic following the initial packet filtration process that identifies abnormal traffic. …”
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  17. 17
    A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features

    A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features by Keshkeh, Kinan

    Published 2022
    “…This study also investigates TLSMalDetect detection performance using seven ML classification algorithms and identifies the one with the highest accuracy.…”
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  18. 18
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
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  19. 19
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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  20. 20
    Cooperative spectrum sensing based on machine learning in cognitive radio vehicular network / Mohammad Asif Hossain

    Cooperative spectrum sensing based on machine learning in cognitive radio vehicular network / Mohammad Asif Hossain by Mohammad Asif , Hossain

    Published 2022
    “…Few examples are energy detection, cyclostationary detection, matched filter detection, etc. …”
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