Search Results - (( pattern detection service algorithm ) OR ( java application optimisation algorithm ))
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK
Published 2011“…This thesis presents new intrusion prevention and self-healing system (SH) for critical services network security. The design features of the proposed system are inspired by the human immune system, integrated with pattern recognition nonlinear classification algorithm and machine learning. …”
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Thesis -
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Hybrid Classification Algorithm For Denial Of Service Attack Detection Using Rough Set Theory And Artificial Immune
Published 2024thesis::master thesis -
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Anomaly detection of denial-of-service network traffic attacks using autoencoders and isolation forest
Published 2026“…This paper presents an unsupervised network-based anomaly detection framework that integrates deep autoencoders with the Isolation Forest algorithm. …”
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DeepIoT.IDS: Hybrid deep learning for enhancing IoT network intrusion detection
Published 2021“…Recently, researchers have suggested deep learning (DL) algorithms to define intrusion features through training empirical data and learning anomaly patterns of attacks. …”
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Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system
Published 2022“…Recently, researchers suggested a deep belief network (DBN) algorithm to construct and build a network intrusion detection system (NIDS) for detecting attacks that have not been seen before. …”
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Face detection in image sequence / Noor Diana Abdullah
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Adaptive feature selection for denial of services (DoS) attack
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Conference or Workshop Item -
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An enhanced android botnet detection approach using feature refinement
Published 2019“…The obtained results show that by using the additional features the detection accuracy improved. The experimental evaluation based on real-world benchmark datasets shows that the selected unique patterns can achieve high detection accuracy with low false positive rate. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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ios Mobile Malware Deep Analysis And Classification For Social Media And Online Banking Exploitation
Published 2024thesis::master thesis -
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SYN Flood detection via machine learning / Muhammad Muhaimin Aiman Mazlan
Published 2018“…Recently, one the most popular attack is denial of service (DoS) that attempt to be malicious pattern to compromise a server or a network resource. …”
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Student Project -
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Energy Efficient High-Performance Computing Aware Proactive Dynamic Virtual Machine Consolidation Technique in Cloud Computing
Published 2022“…The proposed approach, Energy-Aware Multi-Dimensional Online Bin Packing (EAMDOBP), was tested against Power-aware best fit decreasing algorithm (PABFD), Modified Worst Fit decreasing algorithm (MWFD) and Hybrid Local Regression Host Overload Detection (HLRHOD). …”
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Q-Learning-based detection of IPv6 intrusions: a behavioral and performance study
Published 2025“…This problem can significantly affect local network performance or completely deny service to targeted servers. While numerous studies have proposed intrusion detection systems based on supervised learning models, a critical limitation persists. …”
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An early warning system for students at risk using supervised machine learning
Published 2024“…Besides, this study also focuses on the Decision Tree, Random Forest, and XGBoost models in the system. The system will detect or forecast symptoms of dropout or potential dangers ahead of time, allowing educational institutions to anticipate problems and provide adequate educational services through appropriate intervention and response. …”
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