Ammar Alazab

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Affiliation

Centre for Artificial Intelligence and Optimization, DCT, Torrens University, Sydney, NSW, Australia

Topic

Intrusion Detection System,Concept Drift,Data Streams,Ensemble-based Methods,Internet Of Things,Intrusion Detection,Learning Algorithms,Machine Learning,Memory Consumption,5G Networks,Abnormal Behavior,Anomaly Detection,Authors Of This Paper,Base Classifiers,Base Station,Bhattacharyya Distance,Big Data Analytics,Blacklist,Bluetooth,Business Intelligence,Changes In Data,Changes In Distribution,Class Labels,Community Healthcare,Community Perceptions,Computation Time,Customer Information,Cyber Defense,Data Distribution,Data Rate,Data Stream Mining,Deep Neural Network,Defense Mechanisms,Definition Of Security,Delivery Methods,Detection Accuracy,Detection System,Diagnostic Accuracy,Diverse Classification,Diversity Measures,Domain Shift,Drift Model,Energy Consumption,Energy Efficiency,Ensemble Members,Ensemble Method,Environmental Education,Ethnic Background,External Body,External Force,

Biography

Ammar Alazab is currently a Senior Cybersecurity Lecturer with a wealth of industry experience. His expertise extends beyond academia, as he has a strong background in the cybersecurity industry. This practical experience enriches his teaching and research, providing valuable real-world insights to his students. With numerous published articles and over 50 research papers in top-tier journals and conferences, he is a prominent figure in the cybersecurity field. His remarkable contributions have led him to secure research grants amounting to over one million from reputed industry players, further validating the practical significance of his work. His current research interests include cyber security, digital forensics of computer systems, and cybercrime detection and prevention.