Search Results - (( simulation optimization _ algorithm ) OR ( security classification using algorithm ))
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PV fault classification: Impact on accuracy performance using feature extraction in random-forest cross validation algorithm
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. …”
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Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean
Published 2007“…Simulation runs demonstrate that our algorithm leads to better results than the traditional algorithms for scheduling policies used in Grid environment.…”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Malicious URL classification using artificial fish swarm optimization and deep learning
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. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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SVM driven approach for detecting DoS attacks in SDN environment
Published 2025“…To address this challenge, we propose a novel approach that efficiently detects DoS attacks by implementing a packet inspection process using a queuing mechanism, followed by machine learning classification using SVM and KNN algorithms. …”
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Symmetric Key Size for Different Level of Information Classification
Published 2006“…Therefore confidential information is normally protected by using cryptographic algorithms. In these algorithms, key is an important element since it is one of the parameters that determine the level of security that the algorithms can provide. …”
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ChoCD : Usable and secure graphical password authentication scheme
Published 2024thesis::master thesis -
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Security alert framework using dynamic tweet-based features for phishing detection on twitter
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. …”
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An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]
Published 2022“…The IDS with machine learning method improves the detection accuracy of the security attacks. To this end, this paper studies the classification analysis of intrusion detection using various supervised learning algorithms such as SVM, Naive Bayes, KNN, Random Forest, Logistic Regression and Decision tree on the NSL-KDD dataset. …”
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A new mobile botnet classification based on permission and API calls
Published 2024Conference Paper -
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Power system security assessment using artificial neural network: article / Mohd Fathi Zakaria
Published 2010“…This paper presented an application of Artificial Neural Network (ANN) in steady state stability classifications. A multi layer feed forward ANN with Back Propagation Network algorithm is proposed in determining the steady state stability classifications. …”
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K-NN classifier for data confidentiality in cloud computing
Published 2014“…The RSA algorithm is used to encrypt the sensitive data to keep it secure. …”
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Crytojacking Classification based on Machine Learning Algorithm
Published 2024journal::journal article -
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A New Model For Network-Based Intrusion Prevention System Inspired By Apoptosis
Published 2024thesis::doctoral thesis -
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A framework for classification software security using common vulnerabilities and exposures
Published 2018“…This inclusive of the investigation of vulnerability classification objectives,processes,classifiers and focus domains among prominent framework.Final step is to construct the framework by establishing the formal presentation of the vulnerability classification algo-rithm.The validation process was conducted empirically using statistical method to assess the accuracy and consistency by using the precision and recall rate of the algorithm on five data sets each with 500 samples.The findings show a significant result with precision's error rate or p value is between 0.01 and 0.02 with error rate for recall's error rate is between 0.02 and 0.04.Another validation was conducted to verify the correctness of the classification by using expert opinions,and the results showed that the ambiguity of several cases were subdue. …”
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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. …”
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