Preface. Dedication and Acknowledgment. Author. Acronyms. 1. An Overview of Digital Forensics. 2. An Introduction to Machine Learning and Deep Learning for Digital Forensics. 3. Digital Forensics and Computer Foundations. 4. Fundamentals of Hard Disk Analysis. 5. Advanced Hard Disk Analysis. 6. File System Analysis (Windows). 7. Digital Forensics Requirements and Tools. 8. File Allocation Table (FAT) File System. 9. NTFS File System. 10. FAT and NTFS Recovery. 11. Basic Linux for Forensics. 12. Advanced Linux Forensics. 13. Network Forensics. 14. Machine Learning Trends for Digital Forensics. Index.
Summary:
Digital forensics plays a crucial role in identifying, analysing, and presenting cyber threats as evidence in a court of law. Artificial intelligence, particularly machine learning and deep learning, enables automation of the digital investigation process. This book provides an in-depth look at the fundamental and advanced methods in digital forensics. It also discusses how machine learning and deep learning algorithms can be used to detect and investigate cybercrimes. This book demonstrates digital forensics and cyber-investigating techniques with real-world applications. It examines hard disk analytics and style architectures, including Master Boot Record and GUID Partition Table as part of the investigative process. It also covers cyberattack analysis in Windows, Linux, and network systems using virtual machines in real-world scenarios. Digital Forensics in the Era of Artificial Intelligence will be helpful for those interested in digital forensics and using machine learning techniques in the investigation of cyberattacks and the detection of evidence in cybercrimes.
This resource is supported by the Institute of Museum and Library Services under the provisions of the Library Services and Technology Act as administered by State Library of Iowa.