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Digital Forensic Tool Capability

Written by Stephanie Brennadiva and Bryan Cusack

Digital Forensic Tool Capability

Digital forensic tools are trusted to deliver complete data sets for evidential purposes but testing shows variations that impact consistency and scope. Tool

manufacturers constantly bring out updates, patches, and new versions of tools to improve performance. Competition between vendors accelerates tool capability and a comparison of tools over a ten-year period shows innovation and capability growth. In our research we took two industry standard tools and applied them to evidence extraction in the emergent area of social networking forensics. The results showed variation between the tools and also capability limitations. One of the vital elements that digital forensics investigators needed in order to perform an effective forensics investigation is have knowledge of the right tool for each context and case. 

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Featured Book

Learning iOS Forensics

A practical hands-on guide to acquire and analyse iOS devices with the latest forensic techniques and tools.

Meet the Authors

Dr Tim Watson

Dr Tim Watson is the head of the Department of Computer Technology at De Montfort University

 

Coming up in the Next issue of Digital Forensics Magazine

Coming up in Issue 40 on sale from August 2019:


Forensic Syntactical & Linguistic Investigation

Mark Iwazko presents a case study regarding a Forensic Syntactical & Linguistic investigation: Instructed by the Moscow General Council of one of the actual big four accountants. Read More »

Forensic Readiness: A Proactive Approach to Support Forensic Digital Analysis

An increasing number of criminal actions are inflicting financial and brand damage to organizations around the globe. An impressive number of such cases do not reach the courts, mainly because of the organization’s inefficiency to produce robust digital evidences that are acceptable in the courts of law. Read More »

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Using Error-Patterns for Attribution: An Applied Linguistics Technique

Corpus Linguistics within Second Language Acquisition has developed models of error patterns made by defined groups of second language learners. This knowledge base can be leveraged by a knowledgeable analyst to attribute content to a subset of authors. Read More »

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