Search Results - (( security classification model algorithm ) OR ( java application learning algorithm ))

Refine Results
  1. 1

    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. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Symmetric Key Size for Different Level of Information Classification by Ibrahim, Subariah, Maarof, Mohd. Aizaini

    Published 2006
    “…By using this model, we then propose key sizes for different levels of information classification.…”
    Get full text
    Get full text
    Conference or Workshop Item
  3. 3

    Security alert framework using dynamic tweet-based features for phishing detection on twitter by Liew, Seow Wooi

    Published 2019
    “…This framework is divided into three phases which are classification model of phishing detection, detection algorithm of phishing tweet detection and security alert mechanism of phishing tweet detection. …”
    Get full text
    Get full text
    Thesis
  4. 4
  5. 5
  6. 6
  7. 7

    PV fault classification: Impact on accuracy performance using feature extraction in random-forest cross validation algorithm by Muhamad Zahim, Sujod, Siti Nor Azlina, Mohd Ghazali, Mohd Fadzil, Abdul Kadir, Al-Shetwi, Ali Qasem

    Published 2024
    “…This paper introduces a Solar PV Smart Fault Diagnosis and Classification (SFDC) model that harnesses the Random Forest (RF) algorithm in conjunction with Cross-Validation (CV) and an optimized feature extraction (FE) set. …”
    Get full text
    Get full text
    Get full text
    Article
  8. 8

    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
    “…This study proposes a new binary classification model for intrusion detection, based on hybridization of Artificial Bee Colony algorithm (ABC) and Dragonfly algorithm (DA) for training an artificial neural network (ANN) in order to increase the classification accuracy rate for malicious and non-malicious traffic in networks. …”
    Get full text
    Get full text
    Get full text
    Article
  9. 9
  10. 10

    Data classification based on confidentiality in virtual cloud environment by Zardari, M.A., Jung, L.T., Zakaria, M.N.B.

    Published 2014
    “…It is very difficult to decide (in cloud) which data need what security and which data do not need security. However it will be easy to decide the security level for data after data classification according to their security level based on the characteristics of the data. …”
    Get full text
    Get full text
    Article
  11. 11
  12. 12

    BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK by MOHAMED AHMED ELSHEIK, MUNA ELSADIG

    Published 2011
    “…Secondly, specification language, system design, mathematical and computational models for IPS and SH system are established, which are based upon nonlinear classification, prevention predictability trust, analysis, self-adaptation and self-healing algorithms. …”
    Get full text
    Get full text
    Thesis
  13. 13

    Metaheuristic based ids using multi-objective wrapper feature selection and neural network classification by Ghanem, W.A.H.M, El-Ebiary, Y.A.B., Abdulnab, M., Tubishat, M., Alduais, N.A.M., Nasser, A.B., Abdullah, N., Al-wesabi, O.A.

    Published 2021
    “…This article proposes a cyber-intrusion detecting system classification with MLP trained by a hybrid metaheuristic algorithm and feature selection based on multi-objective wrapper method. …”
    Get full text
    Get full text
    Conference or Workshop Item
  14. 14
  15. 15

    Malicious URL classification using artificial fish swarm optimization and deep learning by Mustafa Hilal, Anwer, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, K. Nour, Mohamed, M. Asiri, Mashael, M. Al-Sharafi, Ali, Othman, Mahmoud, Motwakel, Abdelwahed

    Published 2023
    “…With this motivation, the current article develops an Artificial Fish Swarm Algorithm (AFSA) with Deep Learning Enabled Malicious URL Detection and Classification (AFSADL-MURLC) model. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  16. 16
  17. 17

    SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

    Published 2016
    “…But irrelevant and redundant features are the obstacle for classification algorithm to build an efficient detection model. …”
    Get full text
    Get full text
    Conference or Workshop Item
  18. 18

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

    Published 2022
    “…This causes the classifier to be biased, reduce classification accuracy, and increase false alert. To that end, we proposed a model that significantly improve the accuracy of the intrusion detection system by eliminating false alerts, whether they are false negative or false positive negative alerts. …”
    Get full text
    Get full text
    Get full text
    Article
  19. 19
  20. 20

    Android Mobile Malware Surveillance Exploitation Via Call Logs: Proof of Concept by Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan, Nurlida Basir, Nur Fatin Nabila Mohd Rafei Heng, Sakinah Ali Pitchay, Ahmad, IN

    Published 2024
    “…In the future, this new system call classification could be used as a basis to develop a new model to detect mobile attacks exploitation via call logs.…”
    Proceedings Paper