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  1. 1
    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
    “…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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  2. 2
    A study on advanced statistical analysis for network anomaly detection

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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  3. 3
    Machine learning algorithms in context of intrusion detection

    Machine learning algorithms in context of intrusion detection by Mehmood, T., Rais, H.B.Md.

    Published 2016
    “…These machine learning algorithms develop a detection model in a training phase. …”
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  4. 4
    An immune-genetic algorithm with tabu local search for network intrusion detection system / Hamizan Suhaimi

    An immune-genetic algorithm with tabu local search for network intrusion detection system / Hamizan Suhaimi by Suhaimi, Hamizan

    Published 2021
    “…The performance of the proposed method and other existing techniques (Genetic Algorithm, Artificial Immune System and Immune-Genetic Algorithm) were analysed to evaluate and determine its efficiency in terms of maximum intrusion detection rate and the highest true positive rate. …”
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  5. 5
    An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm

    An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm by Abdulkareem, Fatimah Saleem, Mohd Sani, Nor Fazlida

    Published 2023
    “…Therefore, an intrusion detection method for attacking and detecting anomalies in an IoT system must be enhanced. …”
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  6. 6
    Integrating genetic algorithms and fuzzy c-means for anomaly detection

    Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

    Published 2005
    “…In this paper we propose an intrusion detection method that combines Fuzzy Clustering and Genetic Algorithms. …”
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  7. 7
    Experimental evaluation of data fusion algorithm for residual generation in detecting UAV servo actuator fault

    Experimental evaluation of data fusion algorithm for residual generation in detecting UAV servo actuator fault by Sahwee Z., Rahman N.A., Sahari K.S.M.

    Published 2023
    “…Algorithms; Data fusion; Hardware; Military vehicles; Redundancy; Software reliability; Unmanned aerial vehicles (UAV); Analytical redundancy; Data fusion algorithm; Experimental evaluation; Fault detection algorithm; Hostile environments; Model reference methods; On-board fault detection; Software and hardwares; Fault detection…”
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  8. 8
    Methods of intrusion detection in information security incident detection: a comparative study

    Methods of intrusion detection in information security incident detection: a comparative study by Tan, Fui Bee, Yau, Ti Dun, M. N. M., Kahar

    Published 2018
    “…These algorithms and methods provide fast and high rate of detection. …”
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  9. 9
    Features selection for intrusion detection system using hybridize PSO-SVM

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

    Published 2016
    “…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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  10. 10
    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
    “…Moreover, shortage of reliable methods on a new dataset for the intrusion detection system and anomaly detection in terms of classification is an issue. …”
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  11. 11
    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques

    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

    Published 2011
    “…A series of experimental results demonstrate that the proposed intrusion detection model can effectively detect anomalies with low false positive rate, high detection rate and achieve high detection accuracy.…”
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  12. 12
    An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons

    An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons by Ghanem, Waheed Ali H. M., Aman, Jantan, Ahmed Ghaleb, Sanaa Abduljabbar, Naseer, Abdullah B.

    Published 2020
    “…One of the most persistent challenges concerning network security is to build a model capable of detecting intrusions in network systems. …”
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  13. 13
    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
    “…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. The proposed system is designed to detect ginger plants and track their growth rate effectively. …”
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  14. 14
    An efficient anomaly intrusion detection method with evolutionary neural network

    An efficient anomaly intrusion detection method with evolutionary neural network by Sarvari, Samira

    Published 2020
    “…The third proposed method is a new Evolutionary Neural Network (ENN) algorithm with a combination of Genetic Algorithm and Multiverse Optimizer (GAMVO) as a training part of ANN to create efficient anomaly-based detection with low false alarm rate. …”
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  15. 15
    A new intelligent multilayer framework for insider threat detection

    A new intelligent multilayer framework for insider threat detection by Ahmad, Rabiah, Al-Mhiqani, Mohammed Nasser Ahmed, Zainal Abidin, Zaheera, Abdulkareem, Karrar Hameed, Mohammed, Mazin Abed, Gupta, Deepak K., Shankar K.

    Published 2021
    “…The selection procedure has been developed based on the integration of the entropy-VIKOR methods. For the second layer, a hybrid insider threat detection method has been proposed, where the Misuse Insider Threat Detection (MITD) model has been created using the random forest algorithm. …”
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  16. 16
    Feature selection in intrusion detection, state of the art: A review

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

    Published 2016
    “…With irrelevant and redundant features learning algorithm builds detection model with less accuracy rate. …”
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  17. 17
    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
    “…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. The proposed system is designed to detect ginger plants and track their growth rate effectively. …”
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  18. 18
    Ischemic Stroke Detection System With Computer Aided Diagnostic Capability

    Ischemic Stroke Detection System With Computer Aided Diagnostic Capability by Lina, Tay

    Published 2017
    “…MATLAB are used to develop signal processing algorithm of the system. In this project, there are four detection methods investigated. …”
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  19. 19
    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
    “…Traditional anomaly detection algorithms require a set of purely normal data from which they train their model. …”
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  20. 20
    Customer analysis with machine vision

    Customer analysis with machine vision by Tiong, Wei Jie

    Published 2023
    “…This study aimed to improve the human detection model by eliminating the imperfections in existing models that have a high false rate in detecting the cartoons as humans. …”
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