The first book on big digital forensic data

Presents a framework for Digital Forensic Data Reduction and Quick Analysis to identify key evidence and intelligence within disparate digital forensic data holdings

Includes a viable and real-world implementable process that reduces the volume of digital forensic data required for triage, review, analysis, presentation, and archival needs

Autorentext

Dr. Darren Quick is a Senior Intelligence Technologist with the Australian Department of Home Affairs and a former Digital Forensic Investigator with the Australian Border Force, and previously an Electronic Evidence Specialist with the South Australia Police. He has undertaken over 650 digital forensic investigations involving many thousands of digital evidence items. In 2012 Darren was awarded membership of the Golden Key International Honour Society, in 2014 he received a Highly Commended award from the Australian National Institute of Forensic Science, and in 2015 received the Publication of the Year award from the Australian Institute of Professional Intelligence Officers. Dr. Kim-Kwang Raymond Choo holds the Cloud Technology Endowed Professorship at The University of Texas at San Antonio, is an adjunct associate professor at the University of South Australia, a fellow of the Australian Computer Society, and a senior member of IEEE. He and his team won the Digital Forensics Research Challenge 2015 organized by Germany's University of Erlangen-Nuremberg, and he is the recipient of various awards including the ESORICS 2015 Best Paper Award, the 2014 Highly Commended Award from the Australia New Zealand Policing Advisory Agency, Fulbright Scholarship in 2009, the 2008 Australia Day Achievement Medallion, and the British Computer Society's Wilkes Award in 2008.

Klappentext

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.

Inhalt
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.