Big Digital Forensic Data: Volume 1: Data Reduction Framework and Selective Imaging (SpringerBriefs on Cyber Security Systems and Networks)
暫譯: 大型數位鑑識數據:第一卷:數據減少框架與選擇性影像(SpringerBriefs on Cyber Security Systems and Networks)

Darren Quick, Kim-Kwang Raymond Choo

  • 出版商: Springer
  • 出版日期: 2018-05-07
  • 售價: $2,400
  • 貴賓價: 9.5$2,280
  • 語言: 英文
  • 頁數: 96
  • 裝訂: Paperback
  • ISBN: 9811077622
  • ISBN-13: 9789811077623
  • 相關分類: 資訊安全
  • 海外代購書籍(需單獨結帳)

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商品描述

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.

商品描述(中文翻譯)

本書深入探討大數據對數位鑑識調查所帶來的挑戰,也稱為大型數位鑑識數據。它還建立了在大型鑑識數據分析中使用資料探勘的基礎,包括資料縮減、知識管理、情報及資料探勘原則,以實現數位鑑識調查中的更快速分析。透過從各種現實世界設備收集和組裝測試數據的語料庫,本書概述了大數據縮減的過程,以及證據和情報提取方法。此外,本書還包含了對大量真實數位鑑識數據的實驗結果。本書是數位鑑識從業人員、大數據研究者、網路威脅獵捕與情報、資料探勘及其他相關領域的寶貴資源。