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  1. 1

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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    Thesis
  2. 2

    A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

    Published 2017
    “…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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    Multithreaded Scalable Matching Algorithm For Intrusion Detection Systems by Hnaif, Adnan Ahmad Abdelfattah

    Published 2010
    “…Hence, this thesis defines a new algorithm called the Distributed Packet Header Matching algorithm (DPHM), and a New Network Intrusion Detection Systems (NNIDS) platform using hybrid technology in order to increase the overall performance of SNORT-NIDS.…”
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    Thesis
  5. 5

    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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  6. 6

    An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons by Ghanem, Waheed Ali H. M., Aman, Jantan, Ahmed Ghaleb, Sanaa Abduljabbar, Naseer, Abdullah B.

    Published 2020
    “…The issue has been extensively addressed in uncountable researches and using various techniques, of which a commonly used technique is that based on detecting intrusions in contrast to normal network traffic and the classification of network packets as either normal or abnormal. …”
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    Article
  7. 7

    Feature-based face recognition system using utilized artificial neural network by Chai, Tong Yuen

    Published 2010
    “…First, the algorithm will detect a human face and irises. Second, the mouth region is estimated by using geometric calculation based on the irises positions. …”
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    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

    Published 2011
    “…This research investigates the use of a promising technique from machine learning to designing the most suitable intrusion detection for this challenging network type. …”
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  10. 10

    An immune-genetic algorithm with tabu local search for network intrusion detection system / Hamizan Suhaimi by Suhaimi, Hamizan

    Published 2021
    “…This issue highlights the need to tackle the network intrusion problem efficiently. This research aim is to study the performance of an improvised Genetic Algorithm (GA) by formulating its problem-specific algorithm for network intrusion problem. …”
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  11. 11

    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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  12. 12

    Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

    Published 2015
    “…Due to the prevailing limitations of finding novel attacks, high false detection, and accuracy in previous intrusion detection approaches, this study has proposed a hybrid intelligent approach for network intrusion detection based on k-means clustering algorithm and support vector machine classification algorithm. …”
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    Thesis
  13. 13

    Effect Of The Addition Of Wastepaper To Concrete Mix by Shukeri, Ritzawaty Mohamad

    Published 2009
    “…Hence, this thesis defines a new algorithm called the Distributed Packet Header Matching algorithm (DPHM), and a New Network Intrusion Detection Systems (NNIDS) platform using hybrid technology in order to increase the overall performance of SNORT-NIDS.…”
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    Thesis
  14. 14

    Hybrid honey badger algorithm with artificial neural network (HBA-ANN) for website phishing detection by Muhammad Arif, Mohamad, Muhammad Aliif, Ahmad, Zuriani, Mustaffa

    Published 2024
    “…HBA as metahueristic algorithm is used to optimize the network training process of ANN to improve their performances. …”
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    Article
  15. 15

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

    Published 2016
    “…The proposed FPFaSVM method and TAaM depending on the network traffic analyzer to capture and analyze the network traffics, and a special technique that detects anomalies while monitoring network traffics have been proposed by both methods using DARPA 99 dataset and real environments. …”
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    Forgery detection in medical images using Complex Valued Neural Network (CVNN) by Olanrewaju, Rashidah Funke, Khalifa, Othman Omran, Hassan Abdalla Hashim, Aisha, Zeki, Akram M., Aburas, Abdurazzag Ali

    Published 2011
    “…Capabilities of Neural Networks features have been exploited using the Complex version of ANN, trained by Complex backpropagation (CBP) algorithm. …”
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    Article
  18. 18

    Weeds detection for agriculture using Convolutional Neural Network (CNN) algorithm / Khairun Nisa Mohammad Nasir by Mohammad Nasir, Khairun Nisa

    Published 2024
    “…This project aims to develop a weed detection prototype specifically for agricultural settings by utilizing Convolutional Neural Networks (CNN) algorithm. …”
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    Detection Of Misplaced And Missing Regions In Image Using Neural Network by Tan , Jin Siang

    Published 2017
    “…In image processing phase, the captured image is split into regions and the RGB (Red Green Blue) value of the regions is obtained. The neural network used in this research is a back-propagation neural network and it is trained by using Scaled Conjugate Gradient training algorithm. …”
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    Thesis