Oleksandr Lemeshko – författare

This book offers a comprehensive exploration of cutting-edge research and developments in the field of cybersecurity. It presents a curated collection of chapters that reflect the latest in empirical data approximation, malware recognition, information security technologies, and beyond.

Advancements in Cybersecurity: Next-Generation Systems and Applications offers readers a broad perspective on the multifaceted challenges and solutions in contemporary cybersecurity through topics ranging from the application of blockchain technology in securing information systems, to the development of new cost functions for the iterative generation of cryptographic components. The book not only addresses technical aspects but also provides insights into the theoretical frameworks and practical applications that underpin the development of robust cybersecurity systems. It explores the optimization of algorithms for generating nonlinear substitutions, the application of machine learning models for security evaluation, and the implementation of deep learning techniques for detecting sophisticated cyber-attacks. Through its in-depth analysis and forward-looking perspectives, this book contributes significantly to advancing cybersecurity research and practice, paving the way for a safer digital future.

This book is designed to serve as an essential resource for researchers, practitioners, policymakers, and engineers in the fields of ICT, next-generation computing and IT security, including cryptography, AI/ML/DL, cyber resilience, network security, threat modeling and risk assessment, digital forensics, secure software development, hardware security, and human-centric security.

This book offers a comprehensive exploration of cutting-edge research and developments in the field of cybersecurity. It presents a curated collection of chapters that reflect the latest in empirical data approximation, malware recognition, information security technologies, and beyond.

Advancements in Cybersecurity: Next-Generation Systems and Applications offers readers a broad perspective on the multifaceted challenges and solutions in contemporary cybersecurity through topics ranging from the application of blockchain technology in securing information systems, to the development of new cost functions for the iterative generation of cryptographic components. The book not only addresses technical aspects but also provides insights into the theoretical frameworks and practical applications that underpin the development of robust cybersecurity systems. It explores the optimization of algorithms for generating nonlinear substitutions, the application of machine learning models for security evaluation, and the implementation of deep learning techniques for detecting sophisticated cyber-attacks. Through its in-depth analysis and forward-looking perspectives, this book contributes significantly to advancing cybersecurity research and practice, paving the way for a safer digital future.

This book is designed to serve as an essential resource for researchers, practitioners, policymakers, and engineers in the fields of ICT, next-generation computing and IT security, including cryptography, AI/ML/DL, cyber resilience, network security, threat modeling and risk assessment, digital forensics, secure software development, hardware security, and human-centric security.