Mechatronics and Cybersecurity Systems

Intelligent Threat Detection and Digital Trust
Erscheinungsjahr 2027
ISBN: 978-981-9278-97-8
Verlag: Springer

Buch, Englisch, 234 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Emerging Trends in Mechatronics

This book brings together recent research applying intelligent computing to pressing cybersecurity challenges: proactive threat hunting through hybrid deep learning and cyber threat intelligence, blockchain-secured counterfeit detection in smart supply chains, banking fraud detection, unified multi-layer security toolkits, hate speech detection in code-mixed language, electronic voting security architecture, fake news detection and summarization, financial sentiment analysis, and real-time intelligent decision systems. As digital infrastructure grows more networked and mechatronic in nature, spanning banking terminals, voting systems, supply-chain tracking nodes, and industrial endpoints, the attack surface available to bad actors grows with it.

Although these chapters address different attack vectors and domains, they share a common concern: protecting the networked, sensor-rich, and increasingly mechatronic infrastructure that underpins modern digital life. By combining machine learning methodology with practical security engineering, this book equips readers with a broad view of how intelligent computing is strengthening cybersecurity and digital trust across mechatronic and information systems alike.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Agrawal, Akshat

Azizi, Aydin

Fachgebiete

• Technische Wissenschaften Bauingenieurwesen Gebäudesicherheit
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Computerkriminalität & Hacking
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

An Adaptive Hybrid Deep Learning Architecture for Proactive Threat HuntingA Mechatronic Infrastructure Security Framework Utilizing Interpretive CTI Analytics.- Secure and Transparent Counterfeit Detection Using Artificial Intelligence and Blockchain Technology in Mechatronic Smart Supply Chains.- An Intelligent Banking Fraud Detection System Using Rule Based and Machine Learning Techniques for Mechatronic Financial Infrastructure.- Centralized Cyber Security Toolkit An Intelligent Multi Layer Framework for Unified Phishing Detection and Threat Monitoring Across Mechatronic Networks.- Automated Hate Speech Detection for Hindi English Code Mixed Data Using a Hybrid Neural Model Safeguarding Mechatronic Communication Platforms.- Security Architecture of Electronic Voting Systems A Mechatronic Perspective on Trustworthy Digital Infrastructure.

Über Autor(innen)

Dr. Akshat Agrawal obtained his Ph.D. from GGSIPU, Delhi. He is currently working as an associate professor at Computer Science & Engineering, JK Lakshmipat University, Jaipur. Previously, he served as a cluster lead at the School of Computer Science & Engineering, IILM University, Gurugram and served as an assistant professor (Senior Scale) Assistant Professor-III at Amity University Haryana, Amity School of Engineering and Technology. Dr. Agrawal has over 17 years of teaching and research experience. His primary research interests include Artificial Intelligence, Deep Learning, Artificial Neural Networks, Speech Processing, and Image Processing.

Dr. Aydin Azizi holds a Ph.D. in Mechanical Engineering with a specialisation in Mechatronics, a M.Sc. in Mechatronics, and a B.Sc. in Mechanical Engineering. He is a fellow of the Higher Education Academy, an official instructor for the Siemens Mechatronic Systems Certification Program (SMSCP), and an editor-in-chief of the Emerging Trends in Mechatronics book series published by Springer Nature. He currently serves as a senior lecturer and the Academic Partnership Liaison Manager at Oxford Brookes University. His current research focuses on investigating and developing novel techniques to model, control, and optimize complex systems, with expertise in control and automation, artificial intelligence, and simulation techniques.