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Performance evaluation for different intrusion detection system algorithms using machine learning
Published 2018“…The objectives of this project is to evaluate the performance of various intrusion detection algorithms based on machine learning. …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Performance evaluation of intrusion detection system using selected features and machine learning classifiers
Published 2021“…These evolutionary-based algorithms are known to be effective in solving optimization problems. …”
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Polymorphic malware detection based on dynamic analysis and supervised machine learning / Nur Syuhada Selamat
Published 2021“…The most common method of detecting malware relies on signature-based detection. …”
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Multi-sensor fusion based on multiple classifier systems for human activity identification
Published 2019“…To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature vectors from individual sensor modality. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…However, by changing the distribution of both classes, the original classes distribution that are followed by that particular data will be violated. Algorithmic level based methods however are based on introducing new optimization task to improve the minority class classification rate, without changing the data characteristics. …”
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An intelligent DDoS attack detection tree-based model using Gini index feature selection method
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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A stylometry approach for blind linguistic steganalysis model against translation-based steganography
Published 2023“…The performance of the stylometry-based blind steganalysis model is then evaluated based on all false rate, missing rate and accuracy rate and compared against three other standard classifiers in steganalysis; Naive Bayes (NB), k-Nearest Neighbor (k-NN), and Decision Tree (J48). …”
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Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza
Published 2021“…BreakHis is a large and complex dataset (i.e., four subtypes of each benign and malignant BrTs) that publicly available. For BrC detection, an efficient and reliable model namely Ensemble BrC Detection Network (EBrC-Net) and three misclassification reduction (McR) algorithms are developed. …”
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11
Discovering optimal features using static analysis and a genetic search based method for Android malware detection
Published 2018“…Therefore, we used genetic search (GS), which is a search based on a genetic algorithm (GA), to select the features among 106 strings. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease
Published 2021“…Infected palms are asymptomatic throughout the disease's early stages, making disease detection challenging. The survival of affected trees must detect BSR at the mild infected (T1) stage. …”
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13
Discovering optimal features using static analysis and a genetic search based method for Android malware detection
Published 2018“…Therefore, we used genetic search (GS), which is a search based on a genetic algorithm (GA), to select the features among 106 strings. …”
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An improved hybrid learning approach for better anomaly detection
Published 2011“…The recent works has been proposed by Tsai et al. (2010) called a Triangle Area Based Nearest Neighbor (TANN) to obtain high accuracy and detection rate with low false alarms. …”
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Human odour detection approach using machine learning
Published 2019“…Considering the obtained results, employing two hidden layers with more neurons in the hidden layers- to be specific: 15 neurons in every layer- has yielded better accuracy in performance with an accuracy rate of 100%. The unsurpassed framework for learning algorithm to be used for human identification is Levenberg-Marquardt backpropagation learning algorithm. …”
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Optimized Decision Forest for Website Phishing Detection
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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Automated Segmentation And Classification Technique For Brain Stroke
Published 2019“…Pre-processing is applied to the DWI for image normalization, background removal and image enhancement. The algorithm performance has been evaluated using Jaccard Index, Dice Coefficient (DC) and both false positive rate (FPR) and false negative rate (FNR). …”
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Tree-based contrast subspace mining method
Published 2020“…The research works involve first preparing the real world numerical and categorical data sets. Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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Machine learning algorithms in context of intrusion detection
Published 2016“…Although, signature based has high detection rate but it cannot detect novel attacks. …”
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Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti
Published 2024“…The project involves data collection, data preparation, and the implementation of the decision tree algorithm for price prediction. The decision tree's effectiveness and accuracy in predicting laptop prices are evaluated through rigorous testing and validation. …”
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