Adopting an experimental learning approach, this book describes a practical forensic process to acquire and analyze databases from a given device and/or application. Databases hold important, sensitive, and/or confidential information and are a crucial source of evidence in any digital investigation. This also reinforces the importance of keeping up to date on the cyber-threat landscape as well as any associated database forensic challenges and approaches. The book also guides cyber-forensic researchers, educators, and practitioners through the process of conducting database forensics and...
Adopting an experimental learning approach, this book describes a practical forensic process to acquire and analyze databases from a given device and/...
This handbook discusses challenges and limitations in existing solutions, and presents state-of-the-art advances from both academia and industry, in big data analytics and digital forensics. The second chapter comprehensively reviews IoT security, privacy, and forensics literature, focusing on IoT and unmanned aerial vehicles (UAVs). The authors propose a deep learning-based approach to process cloud’s log data and mitigate enumeration attacks in the third chapter. The fourth chapter proposes a robust fuzzy learning model to protect IT-based infrastructure against advanced persistent...
This handbook discusses challenges and limitations in existing solutions, and presents state-of-the-art advances from both academia and industry, in b...
This book constitutes the refereed proceedings of the Second International Conference, UbiSec 2022, held in Zhangjiajie, China, during December 28–31, 2022.The 34 full papers and 4 short papers included in this book were carefully reviewed and selected from 98 submissions. They were organized in topical sections as follows: cyberspace security, cyberspace privacy, cyberspace anonymity and short papers.
This book constitutes the refereed proceedings of the Second International Conference, UbiSec 2022, held in Zhangjiajie, China, during December 28–3...