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This book offers comprehensive insights into digital forensics, guiding readers through analysis methods and security assessments. Expert contributors cover a range of forensic investigations on computer devices, making it an essential resource for professionals, scholars, and students alike.
Chapter 1 explores smart home forensics, detailing IoT forensic analysis and examination of different smart home devices. Chapter 2 provides an extensive guide to digital forensics, covering its origin, objectives, tools, challenges, and legal considerations. Chapter 3 focuses on cyber forensics, including secure chat application values and experimentation. Chapter 4 delves into browser analysis and exploitation techniques, while Chapter 5 discusses data recovery from water-damaged Android phones with methods and case studies. Finally, Chapter 6 presents a machine learning approach for detecting ransomware threats in healthcare systems.
With a reader-friendly format and practical case studies, this book equips readers with essential knowledge for cybersecurity services and operations.
Key Features:
Integrates research from various fields (IoT, Big Data, AI, and Blockchain) to explain smart device security.
Uncovers innovative features of cyber forensics and smart devices.
Harmonizes theoretical and practical aspects of cybersecurity.
Includes chapter summaries and key concepts for easy revision.
Offers references for further study.
Readership:
Professionals, apprentices, teachers, and scholars in cyber security and digital forensics programs.
Chapter 1 explores smart home forensics, detailing IoT forensic analysis and examination of different smart home devices. Chapter 2 provides an extensive guide to digital forensics, covering its origin, objectives, tools, challenges, and legal considerations. Chapter 3 focuses on cyber forensics, including secure chat application values and experimentation. Chapter 4 delves into browser analysis and exploitation techniques, while Chapter 5 discusses data recovery from water-damaged Android phones with methods and case studies. Finally, Chapter 6 presents a machine learning approach for detecting ransomware threats in healthcare systems.
With a reader-friendly format and practical case studies, this book equips readers with essential knowledge for cybersecurity services and operations.
Key Features:
Integrates research from various fields (IoT, Big Data, AI, and Blockchain) to explain smart device security.
Uncovers innovative features of cyber forensics and smart devices.
Harmonizes theoretical and practical aspects of cybersecurity.
Includes chapter summaries and key concepts for easy revision.
Offers references for further study.
Readership:
Professionals, apprentices, teachers, and scholars in cyber security and digital forensics programs.
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