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  1. 1
    An Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Weka

    An Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Weka by Zainal K., Sulaiman N.F., Jali M.Z.

    Published 2024
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  2. 2
    ChoCD : Usable and secure graphical password authentication scheme

    ChoCD : Usable and secure graphical password authentication scheme by Radhi Rafiee Bin Afandi

    Published 2024
    thesis::master thesis
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  3. 3
    Reducing false alarm using hybrid Intrusion Detection based on X-Means clustering and Random Forest classification

    Reducing false alarm using hybrid Intrusion Detection based on X-Means clustering and Random Forest classification by Juma, Sundus, Muda, Zaiton, Yassin, Warusia

    Published 2014
    “…This paper proposed a hybrid machine learning approach based on X-Means clustering and Random Forest classification called XM-RF in order to aforementioned drawbacks. …”
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  4. 4
    Global and local clustering soft assignment for intrusion detection system: a comparative study

    Global and local clustering soft assignment for intrusion detection system: a comparative study by Mohd Rizal Kadis, Azizi Abdullah

    Published 2017
    “…However, the local clustering approach outperforms the global clustering approach on multi-class classification problem. …”
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  5. 5
    Anomaly-based intrusion detection through K-means clustering and naives Bayes classification

    Anomaly-based intrusion detection through K-means clustering and naives Bayes classification by Mohamed Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md. Nasir

    Published 2013
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  6. 6
    Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification

    Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification by Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md Nasir

    Published 2013
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  7. 7
    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…Based on the above components and circumstances, many studies have been performed on data clustering problems. Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
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    Thesis
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  8. 8
    Revolutionizing Perimeter Intrusion Detection: A Machine Learning-Driven Approach with Curated Dataset Generation for Enhanced Security

    Revolutionizing Perimeter Intrusion Detection: A Machine Learning-Driven Approach with Curated Dataset Generation for Enhanced Security by Pitafi, S., Anwar, T., Dewa Made Widia, I., Yimwadsana, B.

    Published 2023
    “…After collecting the data from above mentioned sensors we applied machine learning algorithms DBSCAN to cluster the data points and K-NN classification to classify those clusters in one-dimensional data, but the results were not much satisfying. …”
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  9. 9
    Hybrid intelligent approach for network intrusion detection

    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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  10. 10
    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…Iris is one of the biometric that widely used in the field of security due to its uniqueness. There are a lot of feature extraction methods and classification methods for iris classification. …”
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  11. 11
    An improved hybrid learning approach for better anomaly detection

    An improved hybrid learning approach for better anomaly detection by Mohamed Yassin, Warusia

    Published 2011
    “…The proposed hybrid approach will be clustering all data into the corresponding group before applying a classifier for classification purposes. …”
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  12. 12
    A hybrid framework based on neural network MLP and means clustering for intrusion detection system

    A hybrid framework based on neural network MLP and means clustering for intrusion detection system by Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia

    Published 2013
    “…The hardness of network attacks, as well as their complexity, has also increased lately.High false alarm rate is a big issue for majority of researches in this area.To overwhelm this challenge a hybrid learning approach is proposed, employing the combination of K-means clustering and Neural Network Multi-Layer Perceptron (MLP) classification. …”
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  13. 13
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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    Final Year Project
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  14. 14
    KM-NEU: an efficient hybrid approach for intrusion detection system

    KM-NEU: an efficient hybrid approach for intrusion detection system by Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia, Udzir, Nur Izura

    Published 2014
    “…The K-means clustering algorithm is engaged for grouping analogous nodes into k clusters using the similarity measures such as attack and non-attack, whereas the Neural Network Multi-Layer Perceptron classifies the clustered data into detail categories such as R2L, Probing, DoS, U2R and Normal. …”
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  15. 15
    A hybrid framework based on neural network MLP and K-means clustering for intrusion detection system

    A hybrid framework based on neural network MLP and K-means clustering for intrusion detection system by Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia

    Published 2013
    “…To overwhelm this challenge a hybrid learning approach is proposed, employing the combination of K-means clustering and Neural Network Multi-Layer Perceptron (MLP) classification. …”
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  16. 16
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  17. 17
    Provider independent cryptographic tools

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
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    Monograph
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  18. 18
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    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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  19. 19
    Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean

    Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean by Lorpunmanee, Siriluck, Abdullah, Abdul Razak

    Published 2007
    “…Simulation runs demonstrate that our algorithm leads to better results than the traditional algorithms for scheduling policies used in Grid environment.…”
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  20. 20
    Real-Time Video Processing Using Native Programming on Android Platform

    Real-Time Video Processing Using Native Programming on Android Platform by Saipullah, Khairul Muzzammil

    Published 2012
    “…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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