Search Results - (( java application optimization algorithm ) OR ( security classifications clustering algorithm ))
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ChoCD : Usable and secure graphical password authentication scheme
Published 2024thesis::master thesis -
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Reducing false alarm using hybrid Intrusion Detection based on X-Means clustering and Random Forest classification
Published 2014“…This paper proposed a hybrid machine learning approach based on X-Means clustering and Random Forest classification called XM-RF in order to aforementioned drawbacks. …”
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Global and local clustering soft assignment for intrusion detection system: a comparative study
Published 2017“…However, the local clustering approach outperforms the global clustering approach on multi-class classification problem. …”
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Anomaly-based intrusion detection through K-means clustering and naives Bayes classification
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Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Based on the above components and circumstances, many studies have been performed on data clustering problems. Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
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Revolutionizing Perimeter Intrusion Detection: A Machine Learning-Driven Approach with Curated Dataset Generation for Enhanced Security
Published 2023“…After collecting the data from above mentioned sensors we applied machine learning algorithms DBSCAN to cluster the data points and K-NN classification to classify those clusters in one-dimensional data, but the results were not much satisfying. …”
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Hybrid intelligent approach for network intrusion detection
Published 2015“…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. …”
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…Iris is one of the biometric that widely used in the field of security due to its uniqueness. There are a lot of feature extraction methods and classification methods for iris classification. …”
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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An improved hybrid learning approach for better anomaly detection
Published 2011“…The proposed hybrid approach will be clustering all data into the corresponding group before applying a classifier for classification purposes. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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A hybrid framework based on neural network MLP and means clustering for intrusion detection system
Published 2013“…The hardness of network attacks, as well as their complexity, has also increased lately.High false alarm rate is a big issue for majority of researches in this area.To overwhelm this challenge a hybrid learning approach is proposed, employing the combination of K-means clustering and Neural Network Multi-Layer Perceptron (MLP) classification. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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KM-NEU: an efficient hybrid approach for intrusion detection system
Published 2014“…The K-means clustering algorithm is engaged for grouping analogous nodes into k clusters using the similarity measures such as attack and non-attack, whereas the Neural Network Multi-Layer Perceptron classifies the clustered data into detail categories such as R2L, Probing, DoS, U2R and Normal. …”
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A hybrid framework based on neural network MLP and K-means clustering for intrusion detection system
Published 2013“…To overwhelm this challenge a hybrid learning approach is proposed, employing the combination of K-means clustering and Neural Network Multi-Layer Perceptron (MLP) classification. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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