Search Results - (( security classifications learning algorithm ) OR ( using function method algorithm ))
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Named entity recognition using a new fuzzy support vector machine.
Published 2008“…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
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An efficient anomaly intrusion detection method with evolutionary neural network
Published 2020“…Although activation functions are important for MLP to learn but for nonlinear complex functional mappings it has complicated calculation which reduces the accuracy of classification. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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Security alert framework using dynamic tweet-based features for phishing detection on twitter
Published 2019“…The best phishing classification features and machine learning technique are identified in order to produce and generate a classification model. …”
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Spear- phishing attack detection using artificial intelligence
Published 2024“…The goal is to mitigate phishing and spam threats by using advanced algorithms to detect malicious URLs and classify messages effectively. …”
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Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions
Published 2024Subjects:Article -
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An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]
Published 2022“…The IDS with machine learning method improves the detection accuracy of the security attacks. …”
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A new mobile botnet classification based on permission and API calls
Published 2024Conference Paper -
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Crytojacking Classification based on Machine Learning Algorithm
Published 2024journal::journal article -
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A New Mobile Botnet Classification based on Permission and API Calls
Published 2024Proceedings Paper -
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Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.]
Published 2023“…This study was solely concerned with the Windows malware dataset. The malware classification was determined by testing and training the supervised ML algorithms using the extracted features from the malware dataset. …”
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A novel framework for identifying twitter spam data using machine learning algorithms
Published 2020“…The research results contribute significantly to the field of cyber-security by forming a real-time system using machine learning algorithms.…”
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BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning
Published 2023“…Android (operating system); Android malware; Classification (of information); Feature Selection; Learning systems; Mobile security; Android apps; Classification models; Feature weight; Features selection; Machine learning algorithms; Machine-learning; Malware detection; Malwares; Memory usage; Selection techniques; Learning algorithms…”
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Maldroid- attribute selection analysis for malware classification
Published 2019“…Hence, the objective of this paper is to find the most effective and efficient attribute selection and classification algorithm in malware detection. Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features
Published 2022“…This study also investigates TLSMalDetect detection performance using seven ML classification algorithms and identifies the one with the highest accuracy.…”
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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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