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1
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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2
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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3
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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4
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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5
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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6
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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7
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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8
Optimized clustering with modified K-means algorithm
Published 2021“…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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9
A near-optimal centroids initialization in K-means algorithm using bees algorithm
Published 2009“…The K-mean algorithm is one of the popular clustering techniques.The algorithm requires user to state and initialize centroid values of each group in advance. …”
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10
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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11
Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper -
12
An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem
Published 2021“…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
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13
Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…A comparison was done against particle swarm optimization, genetic algorithm, and sine–cosine algorithm, where the modified cuckoo search algorithm showed the lowest root mean square error and fastest convergence rate among the three algorithms.…”
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14
Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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15
Optimized speed controller for induction motor drive using quantum lightning search algorithm
Published 2023Conference Paper -
16
Cluster optimization in VANET using MFO algorithm and K-Means clustering
Published 2023“…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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17
Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…For optimum results in performance analysis, the optimal value of the MOPSO-CD was evaluated using (ZDT), (WFG), and (DTLZ) with two or three objectives over D2MOPSO, AgMOPSO, MMOPSO, and EMOSO algorithms. …”
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18
Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction
Published 2012“…The proposed KGA model combines greedy algorithm withk-means++ clustering in this research to assist users in automating the finding of the optimal number of new-ons inside the hidden layer of the BP network. …”
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19
Determining optimal location of static VAR compensator by means of genetic algorithm
Published 2011“…The purpose of this paper is to study a practical and accurate heuristic method known as genetic algorithm (GA) which is used to find the optimal location of Static Var Compensator (SVC) and its appropriate size and setting. …”
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20
Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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