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

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

“…The aim of this work is to develop an improved optimization method for IDS that can be efficient and effective in subset feature selection and parameters optimization. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…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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Feature fusion using a modified genetic algorithm for face and signature recognition system by Suryanti, Awang

“…Therefore, the accuracy performance of this system based on the fitness function that will rely on the percentage of correctly recognized samples and the balanced of selected features. Several approaches and benchmark data were used to validate the effectiveness of the proposed method compared to the unimodal system and normal feature selection method. …”
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

“…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. …”

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

“…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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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.

“…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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Harmonic Distortion Prediction Model of a Grid -Connected Photovoltaic Using Grey Wolf Optimizer - Least Square Support Vector Machine by Yasin Z.M., Ashida Salim N., Ab Aziz N.F.

Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by AHMAD, IFTIKHAR

“…Instead of using traditional approach of selecting features with the highest eigenvalues such as PCA, this research applied a Genetic Algorithm (GA) to search the principal feature space that offers a subset of features with optimal sensitivity and the highest discriminatory power. …”
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Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

“…Those problems lend themselves to the realm of optimization. Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
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A Cryptojacking Detection System With Product Moment Correlation Coefficient (Pmcc) Heatmap Intelligent by Kong, Jun Hao

“…However, the feature of the data is too many, lowering the machine-learning detection prediction. Hence, a feature selection method is necessary to pick the right features. …”
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Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by Iftikhar , Ahmad, Azween, Abdullah

“…Instead of using traditional approach of selecting features with the highest eigenvalues such as PCA, this research applied a Genetic Algorithm (GA) to search the principal feature space that offers a subset of features with optimal sensitivity and the highest discriminatory power. …”
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An enhance embedding method using edge and textures detection for image steganography by Al-Maliki, Alaa Jabbar Qasim

“…The study aims to enhance image steganography techniques by using reversible color transformations and optimal area selection within image mosaics to resist statistical attacks. …”
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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.

“…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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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

“…Therefore, an intrusion detection method for attacking and detecting anomalies in an IoT system must be enhanced. …”
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Features selection for IDS in encrypted traffic using genetic algorithm by Barati, Mehdi, Abdullah, Azizol, Mahmod, Ramlan, Mustapha, Norwati, Udzir, Nur Izura

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

“…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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Detection of DDoS attacks in IoT networks using machine learning algorithms by Abdulrahman Alwan, Alwan Ahmed, Shah, Asadullah, Abdulrahman Alwan, Alwan Abdullah, Laghari, Shams Ul Arfeen

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

“…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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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

“…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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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

“…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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