OpenForensics: A digital forensics GPU pattern matching approach for the 21st century

Ethan Bayne*, Robert Ian Ferguson, Adam T. Sampson

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Pattern matching is a crucial component employed in many digital forensic (DF) analysis techniques, such as file-carving. The capacity of storage available on modern consumer devices has increased substantially in the past century, making pattern matching approaches of current generation DF tools increasingly ineffective in performing timely analyses on data seized in a DF investigation. As pattern matching is a trivally parallelisable problem, general purpose programming on graphic processing units (GPGPU) is a natural fit for this problem. This paper presents a pattern matching framework – OpenForensics – that demonstrates substantial performance improvements from the use of modern parallelisable algorithms and graphic processing units (GPUs) to search for patterns within forensic images and local storage devices.

Original languageEnglish
Pages (from-to)S29-S37
JournalDigital Investigation
Volume24
Issue numberSupplement
DOIs
Publication statusPublished - Mar 2018
Event5th Annual DFRWS Europe 2018 - Florence, Italy
Duration: 21 Mar 201823 Mar 2018
https://dfrws.org/conferences/dfrws-eu-2018/

Keywords

  • Asynchronous processing
  • Digital Forensics
  • GPGPU
  • GPU
  • Pattern matching
  • Processing model

ASJC Scopus subject areas

  • Information Systems

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