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  1. 1
    Prevention And Detection Mechanism For Security In Passive Rfid System

    Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

    Published 2013
    “…A GUI is created in a form of JAVA application to display data detected from tag. …”
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  2. 2
    An approach for cross-site scripting detection and removal based on genetic algorithms.

    An approach for cross-site scripting detection and removal based on genetic algorithms. by Hydara, Isatou, Md Sultan, Abu Bakar, Zulzalil, Hazura, Admodisastro, Novia

    Published 2014
    “…In this paper, we propose to explore an approach based on genetic algorithms that will be able to detect and remove cross-site scripting vulnerabilities from the source code before an application is deployed. …”
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  3. 3
    Cross-site scripting detection based on an enhanced genetic algorithm

    Cross-site scripting detection based on an enhanced genetic algorithm by Hydara, Isatou, Md Sultan, Abu Bakar, Zulzalil, Hazura, Admodisastro, Novia Indriaty

    Published 2015
    “…In this paper, we propose to explore an approach based on genetic algorithms that will be able to detect cross-site scripting vulnerabilities in the source code before an application is deployed. …”
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  4. 4
    A multi-filter feature selection in detecting distributed denial-of-service attack

    A multi-filter feature selection in detecting distributed denial-of-service attack by Yon, Yi Jun, Leau, Yu-Beng, Suraya Alias, Park, Yong Jin

    Published 2019
    “…Thus, making it hard to detect and successfully bypasses the detection mechanism. …”
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  5. 5
    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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  6. 6
    An approach to improve detecting and removing cross- site scripting vulnerabilities in web applications

    An approach to improve detecting and removing cross- site scripting vulnerabilities in web applications by Hydara, Isatou

    Published 2015
    “…Many web applications are vulnerable to XSS and are attacked frequently. Most of the previously proposed approaches focused on preventing and detecting XSS attacks during runtime, after vulnerable applications are already deployed. …”
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  7. 7
    Automatic generation of content security policy to mitigate cross site scripting

    Automatic generation of content security policy to mitigate cross site scripting by Mhana, Samer Attallah, Din, Jamilah, Atan, Rodziah

    Published 2016
    “…Content Security Policy (CSP) is powerful client-side security layer that helps in mitigating and detecting wide ranges of web attacks including cross-site scripting (XSS). …”
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  8. 8
    A malware analysis and detection system for mobile devices / Ali Feizollah

    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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  9. 9
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…The performance of the proposed algorithm is also compared to the model developed using the orthogonal least squares (OLS) algorithm. …”
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  10. 10
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…The performance of the proposed algorithm is also compared to the model developed using the orthogonal least squares (OLS) algorithm. …”
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  11. 11
    Model structure selection for a discrete-time non-linear system using genetic algorithm

    Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

    Published 2004
    “…The performance of the proposed algorithm is also compared to the model developed using the orthogonal least squares (OLS) algorithm. …”
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  12. 12
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

    Published 2004
    “…The performance of the proposed algorithm is also compared to the model developed using the orthogonal least squares (OLS) algorithm. …”
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  13. 13
    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control

    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control by Srazhidinov, Radik

    Published 2016
    “…Filtered-X least mean square (FXLMS) control algorithm is a conventional algorithm employed to cancel the noise in linear environment. …”
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  14. 14
    Motion control algorithm development and testing for a free-piston engine generator

    Motion control algorithm development and testing for a free-piston engine generator by Hanipah, M. Razali

    “…This research aims objectives to construct simulation model of a free-piston linear generator for piston motion control algorithm development and testing on a linear actuators prototype. …”
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  15. 15
    Widely linear dynamic quaternion valued least mean square algorithm for linear filtering

    Widely linear dynamic quaternion valued least mean square algorithm for linear filtering by Mohammed, Aldulaimi Haydar Imad

    Published 2017
    “…The performance of the proposed algorithms are compared with quaternion least mean square QLMS, zero-attract quaternion least mean square ZA-QLMS, and widely linear quaternion least mean square WL-QLMS algorithms. …”
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  16. 16
    Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score

    Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score by Mirza Rizwan, Sajid

    Published 2021
    “…This model estimated warped coefficients using the overall linear trend found in linear segments of non-linear relationships. …”
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  17. 17
    Linear-pso with binary search algorithm for DNA motif discovery / Hazaruddin Harun

    Linear-pso with binary search algorithm for DNA motif discovery / Hazaruddin Harun by Harun, Hazaruddin

    Published 2015
    “…However due to the longer time required for complete execution of this algorithm, the Binary Search technique was integrated and a new version of the algorithm was developed, namely the Linear-PSO with Binary Search (LPBS) algorithm. …”
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  18. 18
    Sales prediction for media platforms advertising expenditure using Linear Regression / Nur Athirah Abdurahman

    Sales prediction for media platforms advertising expenditure using Linear Regression / Nur Athirah Abdurahman by Abdurahman, Nur Athirah

    Published 2023
    “…The study focuses on the application of the Linear Regression algorithm to predict sales outcomes based on advertising spending patterns. …”
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  19. 19
    Design of Improved Stream Cipher Algorithms for GSM Communication

    Design of Improved Stream Cipher Algorithms for GSM Communication by Nur Hafiza Zakaria

    Published 2024
    thesis::master thesis
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  20. 20
    Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm

    Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm by Mohamed, M. E, Samir, B. B., Azween, Abdullah

    Published 2010
    “…The algorithm tested use KDD Cup dataset and the result shows a significant improvement in detection accuracy and reducing the false alerts …”
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