Search Results - (( _ application security algorithm ) OR ( its application learning algorithm ))*

Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

“…A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

“…A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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A new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

“…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. The experimental result shows that the Random Forest Algorithm has achieved the highest detection accuracy of 99.4% with the lowest false positive rate of 16.1% as compared to other machine learning algorithms. …”

Deep Learning Based Face Attributes Recognition by Saidi, Mohamad Hazim

“…The automated face identification application is helpful in assisting forensic to survey an area with the implementation of Machine Learning (ML). …”
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Glass break detection system using deep auto encoders with fuzzy rules induction algorithm by Nyein Naing, Wai Yan, Htike, Zaw Zaw

“…While a glass-based material has its advantages, it also poses security risks. Therefore, glass break detectors play an important role in security protection for offices and residential buildings. …”
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A Study On AI-Driven Solutions for Cloud Security Platform by Menaga, Segar, Mohamad Fadli, Zolkipli

“…Cognitive tasks comprise integration, computational cost, and the ethical effect of the algorithm are identified and discussed. Real-world applications and possibilities for further development, such as federated learning and XAI, are also described in order to give recommendations for the effective application of AI-based cloud security. …”
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A comparative analysis of anti-phishing website techniques: identifying optimal approaches to enhance cybersecurity by Yau, Jia Xin

“…The research consists of analysing the characteristics of phishing websites, extracting their essential features using the wrapper method, and classifying websites as phishing or legitimate using supervised and unsupervised learning algorithms. The study evaluates and compares the efficacy of multiple machine learning algorithms, including the Autoencoder classifier, Extreme Gradient Boost (XGBoost), and Random Forest classifier, using metrics such as accuracy, precision, recall, and F1-score. …”
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Fog-cloud scheduling simulator for reinforcement learning algorithms by Al-Hashimi, Mustafa Ahmed Adnan, Rahiman, Amir Rizaan, Muhammed, Abdullah, Hamid, Nor Asilah Wati

“…Fog computing is a popular choice for Internet of Things (IoT) applications, such as electricity, health, transportation, smart cities, security, and more. …”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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Botnet Detection in IoT Devices Using Random Forest Classifier with Independent Component Analysis by Akash, Nazmus Sakib, Rouf, Shakir, Jahan, Sigma, Chowdhury, Amlan, Uddin, Jia

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Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

“…Machine learning method is more famous and applicable than others, because it’s more portable and domain independent. …”
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Efficient Malware Detection And Response Model Using Enhanced Parallel Deep Learning (EPDL-MDR) by Chowdhury Sajadul Islam

'Chapter 7: Smartphone penetration test: Securing Industry 5.0 mobile applications' in "1st Edition, The Future of Human-Computer Integration Industry 5.0 Technology, Tools, and Algorithms". by Eka Wahyu, Aditya, Nur Haryani, Zakaria, Fazli, Azzali, Mohamad Nazim, Jambli

“…The Future of Human-Computer Integration: Industry 5.0 Technology, Tools, and Algorithms provides a valuable insight into how Industry 5.0 technologies, tools, and algorithms can revolutionise industries and drive innovation. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

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Hyperparameter tuned deep learning enabled intrusion detection on internet of everything environment by Ahmed Hamza, Manar, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, S. Alotaibi, Saud, Mahgoub, Hany, S. Mehanna, Amal, Motwakel, Abdelwahed

“…Here, the novelty of the work is the application of MVO algorithm in fine-turning the hyperparameters involved in BiGRU model. …”
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A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features by Keshkeh, Kinan

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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee by Wong , Wen Yee

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PV fault classification: Impact on accuracy performance using feature extraction in random-forest cross validation algorithm by Muhamad Zahim, Sujod, Siti Nor Azlina, Mohd Ghazali, Mohd Fadzil, Abdul Kadir, Al-Shetwi, Ali Qasem

“…As the adoption of solar PV systems continues to surge, the need for robust fault diagnosis and classification techniques becomes paramount to ensure optimal performance, maintenance and scalability across diverse scales of PV arrays in real-world applications. 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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Home intruder detection system using machine learning and IoT by Sahlan, Fadhluddin, Feizal, Faeez Zimam, Mansor, Hafizah

“…The main objectives of HIDES are to create a reliable home security system with the implementation of IoT, to implement the object detection algorithm to determine the presence of humans, and to develop a smart mobile application for users to monitor their houses from anywhere in the world and be alerted if any threats are detected. …”
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