Search Results - (( developing learning optimization algorithm ) OR ( java attack detection algorithm ))

An approach for cross-site scripting detection and removal based on genetic algorithms. by Hydara, Isatou, Md Sultan, Abu Bakar, Zulzalil, Hazura, Admodisastro, Novia

“…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 by Hydara, Isatou, Md Sultan, Abu Bakar, Zulzalil, Hazura, Admodisastro, Novia Indriaty

“…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 by Khor, Jing Huey

“…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 by Yon, Yi Jun, Leau, Yu-Beng, Suraya Alias, Park, Yong Jin

“…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 by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

“…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 by Hydara, Isatou

“…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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Automatic generation of content security policy to mitigate cross site scripting by Mhana, Samer Attallah, Din, Jamilah, Atan, Rodziah

“…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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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

“…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

“…To overcome this problem, Genetic Algorithm (GA) has been used to determine optimal value for BP parameters such as learning rate and momentum rate and also for weight optimization. …”
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

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Operating a reservoir system based on the shark machine learning algorithm by Allawi M.F., Jaafar O., Mohamad Hamzah F., Ehteram M., Hossain M.S., El-Shafie A.

Development of deep reinforcement learning based resource allocation techniques in cloud radio access network by Amjad, Iqbal

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A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection by Basheer G.S., Ahmad M.S., Tang A.Y.C.

“…The multi-agent system applies ant colony optimization and fuzzy logic search algorithms as tools to detecting learning styles. …”

Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition by Yew W.H., Fat Chau C., Mahmood Zuhdi A.W., Syakirah Wan Abdullah W., Yew W.K., Amin N.

“…These DRL-based algorithms optimize the local and global maximum power point (MPP) using deep Q-learning and deep deterministic policy gradient (DDPG). …”

Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Aloufi, Khalid, Kamal Z., Zamli

“…In this paper, a hybrid algorithm of HS with grey wolf optimizer (GWO) has been developed to solve the problem of HS parameter selection. …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications by Chong H.Y., Yap H.J., Tan S.C., Yap K.S., Wong S.Y.