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  1. 1
    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
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  2. 2
    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan

    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 the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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  3. 3
    The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment

    The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment by Nanna Suryana, Herman

    Published 2007
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  4. 4
    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
    “…Data mining is a well-known artificial intelligence technique to build network intrusion detection systems. …”
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  5. 5
    Data mining based damage identification using imperialist competitive algorithm and artificial neural network

    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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  6. 6
    An enhancement of classification technique based on rough set theory for intrusion detection system application

    An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

    Published 2019
    “…An Intrusion Detection System (IDS) is capable to detect unauthorized intrusions into computer systems and networks by looking for signatures of known attacks or deviations of normal activity. …”
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  7. 7
    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak

    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

    Published 2021
    “…A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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  8. 8
    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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  9. 9
    Improving intrusion detection using genetic algorithm

    Improving intrusion detection using genetic algorithm by Hashemi, V. Moraveji, Muda, Zaiton, Yassin, Warusia

    Published 2013
    “…Intrusion Detection System (IDS) is one of the key security components in today’s networking environment. …”
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  10. 10
    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 the increase of internet usage the need of security for organizations network also increased. Network anomaly intrusion detection systems are designed to monitor abnormal activity in the network. …”
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  11. 11
    An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval algorithm

    An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval algorithm by Slamet, ., Izzeldin Ibrahim, Mohamed Abdelaziz

    Published 2022
    “…In IDS, the main problem for nuisance network administrators in detecting attacks is false alerts. …”
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  12. 12
    Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions

    Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

    Published 2024
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  13. 13
    An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs

    An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs by Sadiq, Ali Safaa, Alkazemi, Basem, Mirjalili, Seyedali, Ahmed, Noraziah, Khan, Suleman, Ali, Ihsan, Pathan, Al-Sakib Khan, Ghafoor, Kayhan Zrar

    Published 2018
    “…Our developed algorithm works in extracting the most relevant features that can assist in accurately detecting the network attacks. …”
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  14. 14
    An efficient IDS using hybrid Magnetic swarm optimization in WANETs

    An efficient IDS using hybrid Magnetic swarm optimization in WANETs by Sadiq, Ali Safa, Alkazemi, Basem Y., Mirjalili, Seyedali, Noraziah, Ahmad, Khan, Suleman, Ihsan, Ali, Pathan, Al-Sakib Khan, Ghafoor, Kayhan Zrar

    Published 2018
    “…Our developed algorithm works in extracting the most relevant features that can assist in accurately detecting the network attacks. …”
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  15. 15
    Intrusion detection system for the internet of things based on blockchain and multi-agent systems

    Intrusion detection system for the internet of things based on blockchain and multi-agent systems by Liang, Chao, Shanmugam, Bharanidharan, Azam, Sami, Karim, Asif, Islam, Ashraful, Zamani, Mazdak, Kavianpour, Sanaz, Idris, Norbik Bashah

    Published 2020
    “…The experiment indicates that deep learning algorithms are suitable for intrusion detection in IoT network environment…”
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  16. 16
    An ensemble feature selection method to detect web spam

    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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  17. 17
    Hybrid of fuzzy clustering neural network over NSL dataset for intrusion detection system

    Hybrid of fuzzy clustering neural network over NSL dataset for intrusion detection system by Ahmad Zainaddin, Dahlia Asyiqin, Mohd Hanapi, Zurina

    Published 2013
    “…In recent years, data mining approach for intrusion detection have been advised and used. …”
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  18. 18
    An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval

    An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval by Slamet, Slamet, Izzeldin, Ibrahim Mohamed Abdelaziz

    Published 2022
    “…In IDS, the main problem for nuisance network administrators in detecting attacks is false alerts. …”
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  19. 19
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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  20. 20
    A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications

    A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications by Usmani, U.A., Happonen, A., Watada, J.

    Published 2022
    “…Anomaly detection, sometimes referred to as outlier analysis is a data mining procedure that detects events, data points, and observations that deviates from the expected behaviour of a dataset. …”
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