Framework for Reliable Experimental Design (FRED): A research framework to ensure the dependable interpretation of digital data for digital forensics

Framework for Reliable Experimental Design (FRED): A research framework to ensure the dependable... The establishment of fact forms the cornerstone of any forensic discipline, with digital analysis being no exception. Practitioners are under an obligation as expert witnesses to provide factual accounts of digital scenarios, which must be underpinned by robust knowledge and evidential findings. To achieve this level of reliability, investigatory research must be suitably planned, implemented and analysed in a way which instills confidence in the accuracy of any findings. This is particularly important as digital forensic organisations are now facing the impending requirement to have acquired ISO/IEC 17025 accreditation. This article proposes the Framework for Reliable Experimental Design (FRED) to support those engaged in the field of digital forensics research to contribute reliable, robust findings. FRED focuses on the underpinning procedures involved within undertaking the reverse engineering of digital data structures and the process of extracting and interpreting digital content in a reliable way. The proposed framework is designed to be a resource for those operating within the digital forensic field, both in industry and academia, to support and develop research best practice within the discipline. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computers & Security Elsevier

Framework for Reliable Experimental Design (FRED): A research framework to ensure the dependable interpretation of digital data for digital forensics

Loading next page...
 
/lp/elsevier/framework-for-reliable-experimental-design-fred-a-research-framework-beE6zvsJAh
Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0167-4048
D.O.I.
10.1016/j.cose.2017.11.009
Publisher site
See Article on Publisher Site

Abstract

The establishment of fact forms the cornerstone of any forensic discipline, with digital analysis being no exception. Practitioners are under an obligation as expert witnesses to provide factual accounts of digital scenarios, which must be underpinned by robust knowledge and evidential findings. To achieve this level of reliability, investigatory research must be suitably planned, implemented and analysed in a way which instills confidence in the accuracy of any findings. This is particularly important as digital forensic organisations are now facing the impending requirement to have acquired ISO/IEC 17025 accreditation. This article proposes the Framework for Reliable Experimental Design (FRED) to support those engaged in the field of digital forensics research to contribute reliable, robust findings. FRED focuses on the underpinning procedures involved within undertaking the reverse engineering of digital data structures and the process of extracting and interpreting digital content in a reliable way. The proposed framework is designed to be a resource for those operating within the digital forensic field, both in industry and academia, to support and develop research best practice within the discipline.

Journal

Computers & SecurityElsevier

Published: Mar 1, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off