Buch, Englisch, 398 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 848 g
Reihe: Engineering Cyber-Physical Systems and Critical Infrastructures
Buch, Englisch, 398 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 848 g
Reihe: Engineering Cyber-Physical Systems and Critical Infrastructures
ISBN: 978-3-031-91797-4
Verlag: Springer
This book examines the profound impact of emerging innovations on security and operational effectiveness. This book brings together leading experts in artificial intelligence, blockchain, IoT, and cyber security to tackle key challenges in protecting digital and physical infrastructures. Covering areas such as automated threat detection, secure data exchange, and intelligent system optimization, the book offers practical strategies and case studies. Designed for researchers, professionals, and policymakers, it serves as a comprehensive resource for harnessing advanced technologies to build resilient and efficient security frameworks. Whether mitigating cyber threats, streamlining industrial operations, or improving decision-making, this book provides essential insights for navigating today’s rapidly evolving technological landscape.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
AI-Powered Threat Detection and Prevention.- Cyber Threat Detection and Classification Using Machine Learning Techniques.- A Network Intrusion Detection System using Machine Learning Algorithms.- Enhancing Real-time Security Monitoring: A Hybrid Machine Learning Approach to Cyber Threat Detection.- Hybrid Ensemble Models for Phishing Website Detection: A Comprehensive Comparative Analysis Using varies Classifier Approaches.- Federated Threat Detection with Dirichlet Distribution.- Safeguarding Authenticity: Tackling the Cybersecurity Implications of Deepfake AI.- Evaluating TabNet’s Performance Against Phishing Threats using Deep Learning for Cybersecurity.- Integrating AI, IoT, and Blockchain for Holistic Solutions.- Pragmatic review and Implementation of models targeted toward the identification of fake social media profiles.- Multi- Task Cascaded Convolutional Neural Network Foundation for Driver Drowsiness Detection.- Countering the Imposters: An Efficient Multimodal Approach to Fake Profile Detection on Social Media Sites.
