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  1. 1

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…An Intrusion Detection System is software or application which is used to detect thread, malicious activities and the unauthorized access to the computer system and warn the administrators by generating alarms. …”
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    Thesis
  2. 2

    Dissimilarity algorithm on conceptual graphs to mine text outliers by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

    Published 2009
    “…In Comparison to other text outlier detection method, this approach managed to capture the semantics of documents through the use of CGs and is convenient to detect outliers through a simple dissimilarity function.Furthermore, our proposed algorithm retains a linear complexity with the increasing number of CGs.…”
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    Conference or Workshop Item
  3. 3

    Outlier Detection Technique in Data Mining: A Research Perspective by Mansur, M. O., Md. Sap, Mohd. Noor

    Published 2005
    “…Finding ,removing and detecting outliers is very important in data mining, for example error in large databases can be extremely common, so an important property of a data mining algorithm is robustness with respect to outliers in the database. …”
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    Conference or Workshop Item
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    Effective mining on large databases for intrusion detection by Adinehnia, Reza, Udzir, Nur Izura, Affendey, Lilly Suriani, Ishak, Iskandar, Mohd Hanapi, Zurina

    Published 2014
    “…Data mining is a common automated way of generating normal patterns for intrusion detection systems. …”
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    Conference or Workshop Item
  6. 6

    An ensemble feature selection method to detect web spam by Oskouei, Mahdieh Danandeh, Razavi, Seyed Naser

    Published 2018
    “…Web spam detection is one of research fields of data mining. …”
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    Article
  7. 7

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Experiments demonstrate that ensemble classifier learning method produces better accuracy mining data streams and selecting subset of relevant features comparing other single classifiers. …”
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    Thesis
  8. 8

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

    Published 2019
    “…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
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    Thesis
  9. 9

    Data mining based damage identification using imperialist competitive algorithm and artificial neural network by Gordan, Meisam, Razak, Hashim Abdul, Ismail, Zubaidah, Ghaedi, Khaled

    Published 2018
    “…In this study, to predict the damage severity of sin-gle-point damage scenarios of I-beam structures a data mining based damage identification framework and a hybrid algorithm combining Artificial Neural Network (ANN) and Imperial Competitive Algorithm (ICA), called ICA-ANN method, is proposed. …”
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    Article
  10. 10

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…In this research, a fault diagnosis methodology based on Cross Industry Standard Process for Data Mining (CRISP-DM) model was proposed for the purpose of damage detection. …”
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    Thesis
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    Cancer Prediction Based On Data Mining Using Decision Tree Algorithm by Loh, Kin Ming

    Published 2022
    “…Many studies have been conducted in order to predict cancer. Different data mining method has showed up with its related algorithms were adopted by different research. …”
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    Undergraduates Project Papers
  13. 13

    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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    Unsupervised Anomaly Detection with Unlabeled Data Using Clustering by Chimphlee, Witcha, Abdullah, Abdul Hanan, Md. Sap, Mohd. Noor

    Published 2005
    “…We present a clustering-based intrusion detection algorithm, unsupervised anomaly detection, which trains on unlabeled data in order to detect new intrusions. …”
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    Conference or Workshop Item
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    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…There are many algorithm for analysing clustering each having its own method to do clustering. …”
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    Thesis
  20. 20

    Feature selection in intrusion detection, state of the art: A review by Rais, H.M., Mehmood, T.

    Published 2016
    “…These input features give information to the learning algorithms which used in intrusion detection system in the form of the detection method. …”
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    Article