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    RENTAKA: A novel machine learning framework for crypto-ransomware pre-encryption detection by S. M. M Yassin, S. M. Warusia Mohamed, Abdollah, Mohd Faizal, Mohd, Othman, Ariffin, Aswami

    Published 2022
    “…This study proposed a pre-encryption detection framework for crypto-ransomware using a machine learning approach. …”
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    Article
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    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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    Thesis
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    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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    Conference or Workshop Item
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    A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features by Keshkeh, Kinan

    Published 2022
    “…The difficulty and impracticality of decrypting TLS network traffic before it reaches the Intrusion Detection System (IDS) has driven numerous research studies to focus on anomaly-based malware detection without decryption employing various features and Machine Learning (ML) algorithms. …”
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    Thesis
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    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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    Final Year Project
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    Exploring a Q-learning-based chaotic naked mole rat algorithm for S-box construction and optimization by Kamal Zuhairi, Zamli, Din, Fakhrud, Alhadawi, Hussam S.

    Published 2023
    “…This paper introduces a new variant of the metaheuristic algorithm based on the naked mole rat (NMR) algorithm, called the Q-learning naked mole rat algorithm (QL-NMR), for substitution box construction and optimization. …”
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    Article
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    Implementing server-side federated learning in an edge-cloud framework for precision aquaculture by Ng, Bryan Jing Hong

    Published 2025
    “…In this project, research and literature reviews were conducted to explore the current technologies in smart aquaculture, federated learning, and data privacy. Reviews include systems using IoT and AI-based models, along with analysis of different federated learning algorithms such as FedSGD, FedAvg, and FedProx, and privacypreserving methods such as DA, SA, HE and CKKS encryption. …”
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    Final Year Project / Dissertation / Thesis
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    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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    Thesis
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    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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    Thesis
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    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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    Thesis
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    Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

    Published 2006
    “…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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    Thesis
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    A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features by Keshkeh, Kinan, Jantan, Aman, Alieyan, Kamal

    Published 2022
    “…Due to the complexity of TLS traffic decryption, several anomaly-based detection studies have been conducted to detect TLS-based malware using different features and machine learning (ML) algorithms. …”
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    Article
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