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Cyber Security: An Intelligent Machine Learning Framework for Detecting Distributed Denial-of-Service Attacks in Internet of Things - Softcover
Inhaltsangabe
The rapid proliferation of Internet of Things (IoT) devices has transformed modern digital ecosystems by enabling seamless connectivity and intelligent automation across various domains, including healthcare, transportation, smart cities, and industrial systems. However, the resource-constrained nature and heterogeneous architecture of IoT networks make them highly vulnerable to cyber threats, particularly Distributed Denial-of-Service (DDoS) attacks. These attacks can compromise network availability, disrupt critical services, and cause substantial economic and operational losses. Traditional signature-based intrusion detection approaches often struggle to identify evolving and sophisticated attack patterns, necessitating the development of intelligent and adaptive security solutions. This study proposes an intelligent machine learning framework for detecting DDoS attacks in IoT networks. The framework integrates data preprocessing, feature engineering, and supervised machine learning techniques to effectively distinguish malicious traffic from legitimate network activities.
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Über die Autorin bzw. den Autor
Dr. Emmanuel Ogala holds a Bachelor of Science (B.Sc.), Master of Technology (M.Tech.), and Doctor of Philosophy (Ph.D.) in Computer Science. He is an accomplished academic and researcher with extensive experience in teaching, research, and innovation in computing technologies. His research interests include computer science applications.
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Cyber Security
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Cyber Security : An Intelligent Machine Learning Framework for Detecting Distributed Denial-of-Service Attacks in Internet of Things
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The rapid proliferation of Internet of Things (IoT) devices has transformed modern digital ecosystems by enabling seamless connectivity and intelligent automation across various domains, including healthcare, transportation, smart cities, and industrial systems. However, the resource-constrained nature and heterogeneous architecture of IoT networks make them highly vulnerable to cyber threats, particularly Distributed Denial-of-Service (DDoS) attacks. These attacks can compromise network availability, disrupt critical services, and cause substantial economic and operational losses. Traditional signature-based intrusion detection approaches often struggle to identify evolving and sophisticated attack patterns, necessitating the development of intelligent and adaptive security solutions. This study proposes an intelligent machine learning framework for detecting DDoS attacks in IoT networks. The framework integrates data preprocessing, feature engineering, and supervised machine learning techniques to effectively distinguish malicious traffic from legitimate network activities. Bestandsnummer des Verkäufers 9786630051032
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Cyber Security
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware 76 pp. Englisch. Bestandsnummer des Verkäufers 9786630051032
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Cyber Security | An Intelligent Machine Learning Framework for Detecting Distributed Denial-of-Service Attacks in Internet of Things
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Taschenbuch. Zustand: Neu. Cyber Security | An Intelligent Machine Learning Framework for Detecting Distributed Denial-of-Service Attacks in Internet of Things | Ogala Emmanuel (u. a.) | Taschenbuch | Englisch | 2026 | GlobeEdit | EAN 9786630051032 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 135867829
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