Search Results - (( using optimization model algorithm ) OR ( attack selection method algorithm ))

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  1. 1

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…One of the main steps after the data collection stage of any method is selecting a subset of the features to be used for the feature selection process. …”
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    Thesis
  2. 2

    A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

    Published 2023
    “…For algorithm performance evaluation, the ML-IDS is compared with ML-CICIDS-59 and ML-CICIDS-45, which are IDS trained using the CICIDS-2018 dataset after performing feature engineering. …”
    text::Thesis
  3. 3
  4. 4

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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    Thesis
  5. 5

    A Cryptojacking Detection System With Product Moment Correlation Coefficient (Pmcc) Heatmap Intelligent by Kong, Jun Hao

    Published 2023
    “…Furthermore, a random forest model is used in this study's machine learning classification. …”
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    Undergraduates Project Papers
  6. 6

    Optimized Decision Forest for Website Phishing Detection by Balogun, A.O., Mojeed, H.A., Adewole, K.S., Akintola, A.G., Salihu, S.A., Bajeh, A.O., Jimoh, R.G.

    Published 2021
    “…Nonetheless, given the dynamism of phishing efforts, there is a constant requirement for novel and efficient website phishing detection solutions. In this study, an optimized decision forest (ODF) method for detecting website phishing is proposed ODF involves the use of a genetic algorithm (GA) for the selection of optimal diverse individual trees in a forest to generate an efficient sub-forest. …”
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    Article
  7. 7

    Attacks detection in 6G wireless networks using machine learning by Saeed, Mamoon M., Saeed, Rashid A., Gaid, Abdulguddoos S. A., Mokhtar, Rania A., Khalifa, Othman Omran, Ahmed, Zeinab E.

    Published 2023
    “…The second stage involves the feature selection approach. Correlation Feature Selection algorithm (CFS) is used to implement the suggested hybrid strategy. …”
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    Proceeding Paper
  8. 8

    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

    Published 2022
    “…While the effectiveness of some machine learning algorithms in detecting certain types of network intrusion has been ascertained, the situation remains that no single method currently exists that can achieve consistent results when employed for the detection of multiple attack types. …”
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    Thesis
  9. 9

    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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    Article
  10. 10

    Features selection for IDS in encrypted traffic using genetic algorithm by Barati, Mehdi, Abdullah, Azizol, Mahmod, Ramlan, Mustapha, Norwati, Udzir, Nur Izura

    Published 2013
    “…This paper presents a hybrid feature selection using Genetic Algorithm and Bayesian Network to improve Brute Force attack detection in Secure Shell (SSH) traffic.Brute Force attack traffic collected in a client-server model is implemented in proposed method.Our results prove that the most efficient features were selected by proposed method.…”
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    Conference or Workshop Item
  11. 11

    Features selection for ids in encrypted traffic using genetic algorithm by Barati, Mehdi, Abdullah, Azizol, Mahmod, Ramlan, Mustapha, Norwati, Udzir, Nur Izura

    Published 2013
    “…This paper presents a hybrid feature selection using Genetic Algorithm and Bayesian Network to improve Brute Force attack detection in Secure Shell (SSH) traffic. …”
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    Conference or Workshop Item
  12. 12
  13. 13

    Distributed Denial of Service detection using hybrid machine learning technique by Barati, Mehdi, Abdullah, Azizol, Udzir, Nur Izura, Mahmod, Ramlan, Mustapha, Norwati

    Published 2014
    “…Current paper proposes architecture of a detection system for DDoS attack. Genetic Algorithm (GA) and Artificial Neural Network (ANN) are deployed for feature selection and attack detection respectively in our hybrid method. …”
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    Conference or Workshop Item
  14. 14

    Adaptive feature selection for denial of services (DoS) attack by Yusof, Ahmad Riza'ain, Udzir, Nur Izura, Selamat, Ali, Hamdan, Hazlina, Abdullah @ Selimun, Mohd Taufik

    Published 2017
    “…In this paper, we propose combining two techniques in feature selection algorithm, namely consistency subset evaluation (CSE) and DDoS characteristic features (DCF) to identify and select the most important and relevant features related DDoS attacks. …”
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    Conference or Workshop Item
  15. 15

    An intelligent DDoS attack detection tree-based model using Gini index feature selection method by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik, Atigh, Hayate El

    Published 2023
    “…This paper proposes a novel intelligent DDoS attack detection model based on a Decision Tee (DT) algorithm and an enhanced Gini index feature selection method. …”
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    Article
  16. 16

    Dynamic determinant matrix-based block cipher algorithm by Juremi, Julia

    Published 2018
    “…Analyses on linear, differential and short attack will be performed against the DDBC algorithm to estimate the possible success of all three attacks. …”
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    Thesis
  17. 17

    A multi-filter feature selection in detecting distributed denial-of-service attack by Yon, Yi Jun, Leau, Yu-Beng, Suraya Alias, Park, Yong Jin

    Published 2019
    “…It consists of 3-stage procedures: feature ranking, feature selection and classification. Subsequently, an experimental evaluation of the proposed Multi-Filter Feature Selection (M2FS) method is performed by using the benchmark dataset, NSL-KDD and employed the J48 classification algorithm. …”
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    Conference or Workshop Item
  18. 18

    Steganography based on utilizing more surrounding pixels by Afrakhteh, Masoud

    Published 2010
    “…Conventional LSB method’s concept is used as the benchmark for the proposed algorithms. …”
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    Thesis
  19. 19

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

    Published 2011
    “…In the past decades, machine learning methods have been successfully used in several intrusion detection methods because of their ability to discover and detect novel attacks. …”
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    Thesis
  20. 20

    An improved wavelet digital watermarking software implementation by Khalifa, Othman Omran, Yusof, Yusnita

    Published 2011
    “…This includes general work flow, proposed algorithms for both original method and improved method, which were named as subband matching and selective subband matching, respectively and various attacks performed for evaluation. …”
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    Book Chapter