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  1. 1
    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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  2. 2
    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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  3. 3
    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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  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
    Recursive least square and fuzzy modelling using genetic algorithm for process control application

    Recursive least square and fuzzy modelling using genetic algorithm for process control application by Abdul Rahman, Ribhan Zafira, Yusof, Rubiyah, Khalid, Marzuki

    Published 2007
    “…A technique for the modelling of nonlinear process control using Recursive Least Square and Takagi-Sugeno Fuzzy System with Genetic Algorithm topology is described. …”
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  10. 10
    Optimization of fuzzy model using genetic algorithm for process control application

    Optimization of fuzzy model using genetic algorithm for process control application by Yusof, Rubiyah, Abdul Rahman, Ribhan Zafira, Khalid, Marzuki, Ibrahim, Mohd Faisal

    Published 2011
    “…A technique for the modeling of nonlinear control processes using fuzzy modeling approach based on the Takagi–Sugeno fuzzy model with a combination of genetic algorithm and recursive least square is proposed. …”
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  11. 11
    Modelling and environmental assessment of heterogeneous catalysis biodiesel process using war algorithm

    Modelling and environmental assessment of heterogeneous catalysis biodiesel process using war algorithm by As Eleyana, Ali

    Published 2013
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  12. 12
    Fuzzy modeling using Bat Algorithm optimization for classification

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…Fuzzy modeling is a process of generating parameters which are fuzzy rule and membership function. …”
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  13. 13
    Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm

    Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm by Abdul Sahli, Fakharudin, Norazwina, Zainol, Zulsyazwan, Ahmad Khushairi

    Published 2019
    “…These models were used to find the optimised the network output using genetic algorithm search. …”
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  14. 14
    Mapreduce algorithm for weather dataset

    Mapreduce algorithm for weather dataset by Khalid Adam, Ismail Hammad

    Published 2017
    “…This original dataset is stored in Hadoop Distributed File System. Next, MapReduce Algorithm is developed using Java programming. The algorithm is tested using small and big dataset. …”
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  15. 15
    Development of novel algorithm features in the modelling of cyclic processes

    Development of novel algorithm features in the modelling of cyclic processes by Choong, Thomas S.Y., Paterson, William R., Scott, David M.

    Published 2002
    “…In principle, the algorithm could be used for many cyclic process. Air separation using rapid pressure swing adsorption (RPSA) is used as an illustration. …”
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  16. 16
    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 DQLMS algorithm is extended to the widely linear model forming the WL-DQLMS algorithm in order for the algorithm to be able to capture the full second order statistics. …”
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  17. 17
    SURE-Autometrics algorithm for model selection in multiple equations

    SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

    Published 2016
    “…The SURE-Autometrics is also validated using two sets of real data by comparing the forecast error measures with five model selection algorithms and three non-algorithm procedures. …”
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  18. 18
    Integration of image processing algorithm and deep learning approaches to monitor ginger plant

    Integration of image processing algorithm and deep learning approaches to monitor ginger plant by Tan, Cheng Yong

    Published 2024
    “…The image processing techniques will be used to pre-process and enhance the quality of the images to making it easier for the deep learning model to identify the ginger plants. …”
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  19. 19
    Parametric modelling of twin rotor system using chaotic fractal search algorithm

    Parametric modelling of twin rotor system using chaotic fractal search algorithm by Tuan Abdul Rahman, Tuan Ahmad Zahidi

    Published 2016
    “…The final results found that Chaotic Fractal Search (CFS) algorithm with Gauss/Mouse map shows superiority over other enhanced SFS algorithms when applied both in Diffusion Process and Updating Process.…”
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  20. 20
    Optimisation of fed-batch fermentation process using deep reinforcement learning

    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…The proposed algorithm improves the productivity of yeast while limiting ethanol formation and shows satisfactory performance in dealing with model mismatch and process disturbance.…”
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