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  1. 1
    Outlier Detection Technique in Data Mining: A Research Perspective

    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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  2. 2
    An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach

    An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach by Mohamed Yassin, Warusia

    Published 2015
    “…Detection methods based on statistical and data mining techniques are widely deployed as anomaly-based detection system (ADS). …”
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  3. 3
    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer

    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

    Published 2023
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  4. 4
    Algorithm enhancement for host-based intrusion detection system using discriminant analysis

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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  5. 5
    CHID : conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets

    CHID : conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets by Alaidaros, Hashem Mohammed

    Published 2017
    “…However, flow-based detection still suffers from the generation of the false positive alerts due to incomplete data input. …”
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  6. 6
    Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling

    Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling by Zulaiha Ali Othman, Afaf Muftah Adabashi, Suhaila Zainudin, Saadat M. Al Hashmi

    Published 2011
    “…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. …”
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  7. 7
    An enhanced sequential exception technique for semantic-based text anomaly detection

    An enhanced sequential exception technique for semantic-based text anomaly detection by Taiye, Mohammed Ahmed

    Published 2019
    “…The detection of semantic-based text anomaly is an interesting research area which has gained considerable attention from the data mining community. …”
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  8. 8
    Detecting Duplicate Entry in Email Field using Alliance Rules-based Algorithm

    Detecting Duplicate Entry in Email Field using Alliance Rules-based Algorithm by Arif, Hanafi, Sulaiman, Harun, Enggari, Sofika, Rani, Larissa Navia

    Published 2016
    “…It provides an algorithm to the discovery of error and duplicates entries in the data sets of existing data warehouse. …”
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  9. 9
    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
    “…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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  10. 10
    An Evolutionary Stream Clustering Technique for Outlier Detection

    An Evolutionary Stream Clustering Technique for Outlier Detection by Supardi, N.A., Abdulkadir, S.J., Aziz, N.

    Published 2020
    “…Later, this algorithm will be extended to optimize the model in detecting outlier on data streams. …”
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  11. 11
    Flow-based approach on bro intrusion detection

    Flow-based approach on bro intrusion detection by Alaidaros, Hashem, Mahmuddin, Massudi

    Published 2017
    “…Processing every payload on the wire degrades the performance of intrusion detection. This paper aims to develop a model for reducing the amount of data to be processed by intrusion detection using flow-based approach. …”
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  12. 12
    A clustering-based method for outlier detection under concept drift

    A clustering-based method for outlier detection under concept drift by Tahir, Mahjabeen, Abdullah, Azizol, Udzir, Nur Izura, Kasmiran, Khairul Azhar

    Published 2024
    “…The proposed approach CADSD (Cluster-based Anomaly Detection with Streaming Data), operates in real-time without pre-training. …”
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  13. 13
    Unsupervised Anomaly Detection with Unlabeled Data Using Clustering

    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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  14. 14
    Artificial immune system based on real valued negative selection algorithms for anomaly detection

    Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

    Published 2015
    “…This shows that the Negative Selection Algorithms are equipped with the capabilities of detecting changes in data, thus appropriate for anomaly detection. …”
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  15. 15
    The effect of different similarity distance measures in detecting outliers using single-linkage clustering algorithm for univariate circular biological data

    The effect of different similarity distance measures in detecting outliers using single-linkage clustering algorithm for univariate circular biological data by Nur Syahirah, Zulkipli, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff

    “…Clustering algorithms can be used to create an outlier detection procedure in univariate circular data. …”
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  16. 16
    The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model

    The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari

    Published 2017
    “…In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. …”
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  17. 17
    An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability

    An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability by Bouke, Mohamed Aly, Abdullah, Azizol

    Published 2023
    “…In this paper, we investigate the impact of pattern leakage during data preprocessing on the reliability of Machine Learning (ML) based intrusion detection systems (IDS). …”
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  18. 18
    A Review on feature selection and ensemble techniques for intrusion detection system

    A Review on feature selection and ensemble techniques for intrusion detection system by Torabi, Majid, Udzir, Nur Izura, Abdullah @ Selimun, Mohd Taufik, Yaakob, Razali

    Published 2021
    “…We then analyze and discuss a variety of IDS-based machine learning techniques with various detection models (single classifier-based or ensemble-based), to illustrate their significance and success in the intrusion detection area. …”
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  19. 19
    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
    “…Anomaly-based intrusion detection techniques, that utilize algorithms of machine learning, have the capability to recognize unpredicted malicious. …”
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  20. 20
    Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed

    Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed by Aneesa Ali, Ali Saeed

    Published 2017
    “…The results of the proposed search-based test data generator show significant performance compared to the existing search-based test data generator.…”
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