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Big Digital Forensic Data: Volume 1: Data Reduction Framework and Selective Imaging (Springerbriefs on Cyber Security Systems and Networks)
Darren Quick; Kim-Kwang Raymond Choo (Author)
·
Springer
· Paperback
Big Digital Forensic Data: Volume 1: Data Reduction Framework and Selective Imaging (Springerbriefs on Cyber Security Systems and Networks) - Darren Quick; Kim-Kwang Raymond Choo
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Synopsis "Big Digital Forensic Data: Volume 1: Data Reduction Framework and Selective Imaging (Springerbriefs on Cyber Security Systems and Networks)"
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 analysis and studies a series of intelligence extraction methods. Further, it includes the experimental results on the 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.
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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Paperback.
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