Search Results - (( intrusion detection means algorithm ) OR ( panel optimization method algorithm ))

Search alternatives:

Refine Results
  1. 1
    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
    “…Clustering-based intrusion detection algorithm which trains on unlabeled data in order to detect new intrusions. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  2. 2
    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. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  3. 3
    Hybrid intelligent approach for network intrusion detection

    Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

    Published 2015
    “…Hence, there must be substantial improvement in network intrusion detection techniques and systems. 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. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  4. 4
    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
    “…Anomaly-based intrusion detection methods, which employ machine learning algorithms, are able to identify unforeseen attacks. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  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 Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md Nasir

    Published 2013
    “…Intrusion detection systems (IDSs) effectively balance extra security appliance by identifying intrusive activities on a computer system, and their enhancement is emerging at an unexpected rate.Anomaly-based intrusion detection methods, which employ machine learning algorithms, are able to identify unforeseen attacks. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  6. 6
    Anomaly detection of intrusion based on integration of rough sets and fuzzy c-means

    Anomaly detection of intrusion based on integration of rough sets and fuzzy c-means by Chimphlee, Witcha, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan, Chimphlee, Siriporn

    Published 2005
    “…The objective of this paper is to describe a rough sets and fuzzy c-means algorithms and discuss its usage to detect intrusion in a computer network. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    A hybrid intrusion detection system based on different machine learning algorithms

    A hybrid intrusion detection system based on different machine learning algorithms by Atefi, Kayvan, Yahya, Saadiah, Dak, Ahmad Yusri, Atefi, Arash

    Published 2013
    “…There are numerous study in intrusion detection system (IDS) especially with Genetic algorithms (GA) and Support Vector Machine (SVM) but most of them did not get the potential of hybrid SVM using GA. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  8. 8
    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. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  9. 9
    Improving K-Means Clustering Algorithm Using Discretization Technique in Network Intrusion Detection System (S/O: 13141)

    Improving K-Means Clustering Algorithm Using Discretization Technique in Network Intrusion Detection System (S/O: 13141) by Mohamad Tahir, Hatim, Ghazali, Osman, Katuk, Norliza, Zakaria, Nur Haryani, Omar, Mohd Hasbullah

    Published 2020
    Get full text
    Get full text
    Monograph
    Save to List
    Saved in:
  10. 10
    Improving K-Means Clustering using discretization technique in Network Intrusion Detection System

    Improving K-Means Clustering using discretization technique in Network Intrusion Detection System by Tahir, H.M., Said, A.M., Osman, N.H., Zakaria, N.H., Sabri, P.N.M., Katuk, N.

    Published 2016
    “…An integrated machine learning algorithm using K-Means Clustering with discretization technique and Naïve Bayes Classifier (KMC-D+NBC) is proposed against ISCX 2012 Intrusion Detection Evaluation Dataset. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  11. 11
    Anomaly-based intrusion detection using fuzzy rough clustering

    Anomaly-based intrusion detection using fuzzy rough clustering by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, M. N. M, Srinoy, Surat, Chimphlee, Siriporn

    Published 2006
    “…We apply the idea of the Fuzzy Rough C-means (FRCM) to clustering analysis. FRCM integrates the advantage of fuzzy set theory and rough set theory that the improved algorithm to network intrusion detection. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  12. 12
    A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection

    A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection by Jia, Lu, Yin Chai, Wang, Chee Siong, Teh, Xinjin, Li, Liping, Zhao, Fengrui, Wei

    Published 2022
    “…For generating an interpretable deep architecture for identifying deep intrusion patterns, this study proposes an approach that combines ANFIS (Adaptive Network-based Fuzzy Inference System) and DT (Decision Tree) for interpreting the deep pattern of intrusion detection. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  13. 13
    An improved hybrid learning approach for better anomaly detection

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

    Published 2011
    “…Gaining unauthorized access to files, attempting to damage the network and data, and any other serious security threat must be prevented by the Intrusion Detection System. Anomaly detection is one of intrusion detection techniques. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  14. 14
    An efficient anomaly intrusion detection method with feature selection and evolutionary neural network

    An efficient anomaly intrusion detection method with feature selection and evolutionary neural network by Sarvari, Samira, Mohd Sani, Nor Fazlida, Mohd Hanapi, Zurina, Abdullah @ Selimun, Mohd Taufik

    Published 2020
    “…A proposed model has been practically used to the problem of intrusion detection as well as been validated using the NSL-KDD dataset. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  15. 15
    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
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  16. 16
    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 hardness of network attacks as well as their complexities has also increased lately. The anomaly-based Intrusion Detection Systems (IDS) are able to detect unknown attacks. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  17. 17
    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
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  18. 18
    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…Therefore, the core classifier in the hyper-heuristic approach of Intrusion Detection System (IDS) is developed to the parallel structure NN. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  19. 19
    Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana

    Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana by Hatungimana, Gervais

    Published 2018
    “…Anomaly-based Intrusion Detection System (IDS) uses known baseline to detect patterns which have deviated from normal behaviour. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    A comparative study between deep learning algorithm and bayesian network on Advanced Persistent Threat (APT) attack detection

    A comparative study between deep learning algorithm and bayesian network on Advanced Persistent Threat (APT) attack detection by Ooi, Hui Ni, Ab Rahman, Nurul Hidayah

    Published 2021
    “…This means that Multilayer Perceptron algorithm can detect APT attack more accurately. …”
    Get full text
    Get full text
    Get full text
    Other
    Save to List
    Saved in:

Search Tools: