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Cited 7 time in webofscience Cited 12 time in scopus
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Design and Implementation of a Digital Evidence Management Model Based on Hyperledger Fabric

Authors
Jeong, JunhoKim, DonghyoLee, ByungdoSon, Yunsik
Issue Date
Aug-2020
Publisher
KOREA INFORMATION PROCESSING SOC
Keywords
Blockchain; Digital Evidence Management; Digital Forensic; Hyperledger Fabric; Smart Contract
Citation
JOURNAL OF INFORMATION PROCESSING SYSTEMS, v.16, no.4, pp 760 - 773
Pages
14
Indexed
SCOPUS
ESCI
KCI
Journal Title
JOURNAL OF INFORMATION PROCESSING SYSTEMS
Volume
16
Number
4
Start Page
760
End Page
773
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/6378
DOI
10.3745/JIPS.04.0178
ISSN
1976-913X
2092-805X
Abstract
When a crime occurs, the information necessary for solving the case, and various pieces of the evidence needed to prove the crime are collected from the crime scene. The tangible residues collected through scientific methods at the crime scene become evidence at trial and a clue to prove the facts directly against the offense of the suspect. Therefore, the scientific investigation and forensic handling for securing objective forensic in crime investigation is increasingly important. Today, digital systems, such as smartphones, CCTVs, black boxes, etc. are increasingly used as criminal information investigation clues, and digital forensic is becoming a decisive factor in investigation and trial. However, the systems have the risk that digital forensic may be damaged or manipulated by malicious insiders in the existing centralized management systems based on client/server structure. In this paper, we design and implement a blockchain based digital forensic management model using Hyperledger Fabric and Docker to guarantee the reliability and integrity of digital forensic. The proposed digital evidence management model allows only authorized participants in a distributed environment without a central management agency access the network to share and manage potential crime data. Therefore, it could be relatively safe from malicious internal attackers compared to the existing client/server model.
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