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A Digital Forensic Investigation and Verification Model for Industrial Espionage

  • Jieun Dokko
  • Michael Shin
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 259)

Abstract

This paper describes a digital forensic investigation and verification model for industrial espionage (DEIV-IE) focusing on insider data thefts at the company level. This model aims to advance the state-of practice in forensic investigation and to verify evidence sufficiency of industrial espionage cases by incorporating the crime specific features and analysis techniques of digital evidence. The model is structured with six phases: file reduction, file classification, crime feature identification, evidence mapping, evidence sufficiency verification, and documentations. In particular, we focus on characterizing crime features that have multiple aspects of commonalities in crime patterns in industrial espionage; and the evidence sufficiency verification that is a verification procedure for digital evidence sufficiency for court decision using these crime features. This model has been developed based on analysis of five industrial espionage cases and the literature review, being validated with three additional cases in terms of the effectiveness of the model.

Keywords

Digital forensic investigation Digital evidence verification Evidence prioritization Behavioral evidence analysis Digital forensics triage Industrial espionage 

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  1. 1.Department of Computer ScienceTexas Tech UniversityLubbockUSA
  2. 2.Supreme Prosecutors’ OfficeSeoulRepublic of Korea

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