TY  - BOOK
AU  - Quick,Darren
AU  - Choo,Kim-Kwang Raymond
ED  - SpringerLink (Online service)
TI  - Big Digital Forensic Data: Volume 1: Data Reduction Framework and Selective Imaging 
T2  - SpringerBriefs on Cyber Security Systems and Networks,
SN  - 9789811077630
AV  - QA76.9.A25 
U1  - 005.8 23
PY  - 2018///
CY  - Singapore
PB  - Springer Singapore, Imprint: Springer
KW  - Computer security
KW  - Application software
KW  - Forensic science
KW  - Computers
KW  - Law and legislation
KW  - Systems and Data Security
KW  - Information Systems Applications (incl. Internet)
KW  - Forensic Science
KW  - Legal Aspects of Computing
KW  - Computer Appl. in Social and Behavioral Sciences
N1  - Acceso multiusuario; Chapter 1 Introduction -- Chapter 2 Background and Literature Review -- Chapter 3 Data Reduction and Data Mining Framework -- Chapter 4 Digital Forensic Data Reduction by Selective Imaging -- Chapter 5 Summary of the Framework and DRbSI
N2  - This book provides an in-depth understanding of big data challenges to digital forensic investigations, also known as big digital forensic data. It also develops the basis of using data mining in big forensic data analysis, including data reduction, knowledge management, intelligence, and data mining principles to achieve faster analysis in digital forensic investigations. By collecting and assembling a corpus of test data from a range of devices in the real world, it outlines a process of big data reduction, and evidence and intelligence extraction methods. Further, it includes the experimental results on vast volumes of real digital forensic data. The book is a valuable resource for digital forensic practitioners, researchers in big data, cyber threat hunting and intelligence, data mining and other related areas
UR  - http://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-981-10-7763-0
ER  -