Search Results - (( program learning evolution algorithm ) OR ( java attack detection algorithm ))
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus
Published 2003“…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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An approach for cross-site scripting detection and removal based on genetic algorithms.
Published 2014“…In this paper, we propose to explore an approach based on genetic algorithms that will be able to detect and remove cross-site scripting vulnerabilities from the source code before an application is deployed. …”
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Cross-site scripting detection based on an enhanced genetic algorithm
Published 2015“…In this paper, we propose to explore an approach based on genetic algorithms that will be able to detect cross-site scripting vulnerabilities in the source code before an application is deployed. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…A GUI is created in a form of JAVA application to display data detected from tag. …”
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A multi-filter feature selection in detecting distributed denial-of-service attack
Published 2019“…Thus, making it hard to detect and successfully bypasses the detection mechanism. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications
Published 2025“…Accordingly, the aim of this study is to identify the latest SQL injection attacks based on user’s inputs in web application associated with remote server database, and to develop a new method based on dynamic detection technique to prevent SQL injection attacks. …”
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An approach to improve detecting and removing cross- site scripting vulnerabilities in web applications
Published 2015“…Many web applications are vulnerable to XSS and are attacked frequently. Most of the previously proposed approaches focused on preventing and detecting XSS attacks during runtime, after vulnerable applications are already deployed. …”
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Differential evolution for neural networks learning enhancement
Published 2008“…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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Automatic generation of content security policy to mitigate cross site scripting
Published 2016“…Content Security Policy (CSP) is powerful client-side security layer that helps in mitigating and detecting wide ranges of web attacks including cross-site scripting (XSS). …”
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A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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Performances Of Metaheuristic Algorithms In Optimizing Tool Capacity Allocations
Published 2014“…In this research, the algorithms studied includes Genetic Algorithm, Particle Swarm Optimization Algorithm, Differential Evolution Algorithm, Harmony Search Algorithm, Teaching-LearningBased Optimization Algorithm and Black Hole Algorithm. …”
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An Analysis Of System Calls Using J48 And JRip For Malware Detection
Published 2018“…The evolution of malware possesses serious threat ever since the concept of malware took root in the technology industry.The malicious software which is specifically designed to disrupt,damage,or gain authorized access to a computer system has made a lot of researchers try to develop a new and better technique to detect malware but it is still inaccurate in distinguishing the malware activities and ineffective.To solve the problem,this paper proposed the integrated machine learning methods consist of J48 and JRip in detecting the malware accurately.The integrated classifier algorithm applied to examine,classify and generate rules of the pattern and program behaviour of system call information.The outcome then revealed the integrated classifier of J48 and JRip outperforming the other classifier with 100% detection of attack rate. …”
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An Analysis Of System Calls Using J48 And JRip For Malware Detection
Published 2018“…The integrated classifier algorithm applied to examine, classify and generate rules of the pattern and program behaviour of system call information. …”
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