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Pypette: A Platform for the Evaluation of Live Digital Forensics
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Author(s): Brett Lempereur (School of Computing and Mathematical Sciences, Liverpool John Moores University, Liverpool, UK), Madjid Merabti (School of Computing and Mathematical Sciences, Liverpool John Moores University, Liverpool, UK)and Qi Shi (School of Computing and Mathematical Sciences, Liverpool John Moores University, Liverpool, UK)
Copyright: 2013
Pages: 15
Source title:
Emerging Digital Forensics Applications for Crime Detection, Prevention, and Security
Source Author(s)/Editor(s): Chang-Tsun Li (University of Warwick, UK)
DOI: 10.4018/978-1-4666-4006-1.ch009
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Abstract
Live digital forensics presents unique challenges with respect to maintaining forensic soundness, but also offers the ability to examine information that is unavailable to quiescent analysis. Any perturbation of a live operating system by a forensic examiner will have far-reaching effects on the state of the system being analysed. Numerous approaches to live digital forensic evidence acquisition have been proposed in the literature, but relatively little attention has been paid to the problem of identifying how the effects of these approaches, and their improvements over other techniques, can be evaluated and quantified. In this paper, the authors present Pypette, a novel platform enabling the automated, repeatable analysis of live digital forensic acquisition techniques.
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