Mechatronics and Cybersecurity Systems

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.