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  1. 1
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
    “…Accordingly, the aim of this study is to identify the latest SQL injection attacks based on user’s inputs in web application associated with remote server database, and to develop a new method based on dynamic detection technique to prevent SQL injection attacks. …”
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  2. 2
    An amplitude independent muscle activity detection algorithm based on adaptive zero crossing technique and mean instantaneous frequency of the sEMG signal

    An amplitude independent muscle activity detection algorithm based on adaptive zero crossing technique and mean instantaneous frequency of the sEMG signal by Hameed, Husamuldeen Khalid, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina

    Published 2017
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  3. 3
    Propose a new firefly-fast learning network model based intrusion-detection system

    Propose a new firefly-fast learning network model based intrusion-detection system by Badran, Mohammed Falih, Moorthy, Kohbalan, Zukifi, Nor Saradatul Akmar, Mohamad, Mohd Saberi, Deris, Safaai, Md.Sahar, Nan

    Published 2019
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  4. 4
    A new hybrid teaching learning based optimization -extreme learning machine model based intrusion-detection system

    A new hybrid teaching learning based optimization -extreme learning machine model based intrusion-detection system by Alsudani, Mustafa Qahtan, Abbdal Reflish, Salah, Moorthy, Kohbalan, Adnan, Myasar Mundher

    Published 2023
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  5. 5
    A new corner detection algorithm for chain code representation.

    A new corner detection algorithm for chain code representation. by Haron , Habibollah, Shamsuddin , Siti Mariyam, Mohamed, Dzulkifli

    Published 2005
    “…A new algorithm is proposed to detect a corner of a thinned binary image that is represented by an eight-connected contour chain code. …”
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  6. 6
    Integrating genetic algorithms and fuzzy c-means for anomaly detection

    Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

    Published 2005
    “…Clustering-based intrusion detection algorithm which trains on unlabeled data in order to detect new intrusions. …”
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  7. 7
    An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons

    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
    “…However, the problem of improving the accuracy and efficiency of classification models remains open and yet to be resolved. This study proposes a new binary classification model for intrusion detection, based on hybridization of Artificial Bee Colony algorithm (ABC) and Dragonfly algorithm (DA) for training an artificial neural network (ANN) in order to increase the classification accuracy rate for malicious and non-malicious traffic in networks. …”
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  8. 8
    Propose a new Firefly-Fast Learning Network model based Intrusion-Detection System

    Propose a new Firefly-Fast Learning Network model based Intrusion-Detection System by Mohammed Falih, Badran, Kohbalan, Moorthy, Nor Saradatul Akmar, Zulkifli, Mohd Saberi, Mohamad, Safaai, Deris, Nan, Md. Sahar

    Published 2019
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  9. 9
    A new vertical edge detection algorithm and its application

    A new vertical edge detection algorithm and its application by Al-Ghaili, Abbas Mohammed Ali, Mashohor, Syamsiah, Ismail, Alyani, Ramli, Abdul Rahman

    Published 2008
    “…The need to distinguish the desired details is a very important pre-process in order to give good results in short time processing. We proposed a new and fast vertical edge detection algorithm (VEDA) which is based on the contrast between the gray scale values. …”
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  10. 10
    Automatic detection of lineaments from LANDSAT images in United Arab Emirate (UAE)

    Automatic detection of lineaments from LANDSAT images in United Arab Emirate (UAE) by Marghany , Maged, El Mahdi, Samy Ismail, Hashim, Mazlan

    Published 2006
    “…Lineament identifications from remotely sensed data are required standard procedures. This work utilized a new geomatical tool for lineament identification which based on automatic detection algorithms. …”
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  11. 11
    Propose a new Firefly-Fast Learning Network model based Intrusion-Detection System

    Propose a new Firefly-Fast Learning Network model based Intrusion-Detection System by Badran, Mohammed Falih, Moorthy, Kohbalan, Zukifi, Nor Saradatul Akmar, Mohamad, Mohd Saberi, Deris, Safaai, Md.Sahar, Nan

    Published 2019
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  12. 12
    Improved intrusion detection algorithm based on TLBO and GA algorithms

    Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

    Published 2021
    “…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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  13. 13
    Energy detection for spectrum sensing in OFDM-based cooperative and non-cooperative radio networks

    Energy detection for spectrum sensing in OFDM-based cooperative and non-cooperative radio networks by Salman, Emad Hmood

    Published 2018
    “…This algorithm can also work for big number of SUs that detect the OFDM signal. …”
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  14. 14
    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level

    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

    Published 2024
    thesis::doctoral thesis
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  15. 15
    Development of computer aided three-dimensional geometric modeler based on designer's idea in twodimensional

    Development of computer aided three-dimensional geometric modeler based on designer's idea in twodimensional by Haron, Habibollah

    Published 2006
    “…This study has proposed better solutions in terms of an enhanced thinning algorithm, a modified Freeman chain code and Vertex chain code algorithm as picture description language, and a new computational algorithm and neural network classifier for corner detection. …”
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  16. 16
    Image Based Congestion Detection Algorithms And Its Real Time Implementation

    Image Based Congestion Detection Algorithms And Its Real Time Implementation by Khdiar, Ahmed Nidhal

    Published 2015
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  17. 17
    Improving The Algorithm To Detect Internet Worms

    Improving The Algorithm To Detect Internet Worms by Rasheed, Mohmmad M

    Published 2008
    “…The aim of this project is to improved algorithm to detect internet worm by two sub algorithm. …”
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  18. 18
    Intrusion Detection Systems, Issues, Challenges, and Needs

    Intrusion Detection Systems, Issues, Challenges, and Needs by Aljanabi, Mohammad, Mohd Arfian, Ismail, Ali, Ahmed Hussein

    Published 2021
    “…However, these algorithms suffer from many lacks especially when apply to detect new type of attacks, and need for new algorithms such as JAYA algorithm, teaching learning-based optimization algorithm (TLBO) algorithm is arise. …”
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  19. 19
    Multi-Phase Information Theory-Based Algorithm for Edge Detection of Aerial Images

    Multi-Phase Information Theory-Based Algorithm for Edge Detection of Aerial Images by Elaraby, Ahmed, Al-Ameen, Zohair

    Published 2022
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  20. 20
    Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff

    Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff by Mohd Yusoff, Mohd Izhan

    Published 2014
    “…The new algorithm is tested on simulated and real data where the results show it is capable of detecting fraud activities. …”
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