Digital Forensics in the Era of Artificial Intelligence

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A01=Nour Moustafa
advanced digital evidence techniques
Author_Nour Moustafa
Boot Sectors
Booting Process
Category=JKVF1
Category=PBCD
Category=UBL
Category=URH
Category=UYQ
cybercrime investigation
deep learning
Deep Learning Algorithms
Digital Forensic Investigation
Digital Forensic Tools
Digital Forensics
Digital Forensics Process
Disk Editor
Disk Image
EFI
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
FAT
File Allocation Table
File Named
File Names
File System
file system recovery
forensic data analytics
Forensic Images
forensics
hard disk
Hash Values
IoT Device
IP Protocol Suite
Linux
machine learning
Master File Table
MFT
Multi-class Classification
network intrusion detection
NFTS
Partition Table
partition table analysis
RNN
Slack Space
Ubuntu Server
virtual machine forensics
Windows

Product details

  • ISBN 9781032244686
  • Weight: 380g
  • Dimensions: 156 x 234mm
  • Publication Date: 18 Jul 2022
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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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.

Dr Nour Moustafa is currently Senior Lecturer and leader of Intelligent Security Group at the School of Engineering & Information Technology, University of New South Wales (UNSW Canberra), Australia. He is also Strategic Advisor (AI-SME) at the DXC Technology, Canberra, Australia. He was a Post-doctoral Fellow at UNSW Canberra from June 2017 to December 2018. He received his PhD degree in Computing from UNSW, Australia, in 2017. He obtained his Bachelor and Master degree in Computer Science in 2009 and 2014, respectively, from the Faculty of Computer and Information, Helwan University, Egypt. His areas of interest include Cyber Security, particularly network security, IoT security, intrusion detection systems, statistics, deep learning and machine learning techniques. He has several research grants from industry and defence sponsors, such as Australia's Cyber Security Cooperative Defence Centre, Australian Defence Science and Technology Group, and the Canadian Department of National Defence. He has been awarded the 2020 prestigious Australian Spitfire Memorial Defence Fellowship award. He is also a Senior IEEE Member, ACM Distinguished Speaker, and Spitfire Fellow. He has served his academic community as the guest associate editor of multiple journals, such as IEEE Transactions on Industrial Informatics, IEEE Systems, IEEE IoT Journal, IEEE Access, Ad Hoc Networks, and the Journal of Parallel and Distributed Computing. He has also served over seven leadership conferences, including as vice-chair, session chair, Technical Program Committee (TPC) member and proceedings chair, including for the 2020–2021 IEEE TrustCom and 2020 33rd Australasian Joint Conference on Artificial Intelligence.

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