Digital forensics in the era of artificial intelligence / Nour Moustafa.
Material type:
TextPublisher: Boca Raton, FL ; Abingdon, Oxon : CRC Press, 2023Edition: First editionDescription: xix, 236 pages : illustrations ; 24 cmContent type: - text
- unmediated
- volume
- 9781032244686
- 363.25968 M867d
- HV8078.7 .M68 2023
| Item type | Current library | Shelving location | Call number | Copy number | Status | Date due | Barcode | |
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Main Library | Circulation Section | CIR 363.25968 M867d 2023 (Browse shelf(Opens below)) | 1-1 | Available | 029297 |
Includes bibliographical references and index.
An overview of digital forensics -- An introduction to machine learning and deep learning for digital forensics -- Digital forensics and computer foundations -- Fundamentals of hard disk analysis -- Advanced hard disk analysis -- File system analysis (windows) -- Digital forensics requirements and tools -- File allocation table (FAT) file system -- NTFS file system -- FAT and NTFS recovery -- Basic Linux for forensics -- Advanced Linux forensics -- Network forensics -- Machine learning trends for digital forensics.
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
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