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Published (Version of Record)CC BY V4.0, Open Access
Journal article
IoT Forensics-Based on the Integration of a Permissioned Blockchain Network
Blockchains, Vol.2(4), pp.482-506
2024
Abstract
The proliferation of Internet of Things (IoT) devices has facilitated the exchange of information among individuals and devices. This development has introduced several challenges, including increased vulnerability to potential cyberattacks and digital forensics. IoT forensic investigations need to be managed in a forensically sound manner using a standard framework. However, adopting traditional digital forensics tools introduces various challenges, such as identifying all IoT devices and users at the crime scene. Therefore, collecting evidence from these devices is a major problem. This paper proposes a permissioned blockchain integration solution for IoT forensics (PBCIS-IoTF) that aims to observe data transactions within the blockchain. The PBCIS-IoTF framework designs and tests Hyperledger blockchains simulated with a Raspberry Pi device and chaincode to address the challenges of IoT forensics. This blockchain is deployed using multiple nodes within the network to avoid a single point of failure. The authenticity and integrity of the acquired evidence are analysed by comparing the SHA-256 hash metadata in the blockchain of all peers within the network. We further integrate webpage access with the blockchain to capture the forensics data from the user’s IoT devices. This allows law enforcement and a court of law to access forensic evidence directly and ensures its authenticity and integrity. PBCIS-IoTF shows high authenticity and integrity across all peers within the network.
Details
- Title
- IoT Forensics-Based on the Integration of a Permissioned Blockchain Network
- Authors/Creators
- Butrus Mbimbi - Murdoch UniversityDavid Murray - Murdoch UniversityMichael Wilson - Murdoch University
- Publication Details
- Blockchains, Vol.2(4), pp.482-506
- Publisher
- MDPI AG
- Identifiers
- 991005726478607891
- Copyright
- © 2024 by the authors
- Murdoch Affiliation
- School of Law and Criminology; School of Information Technology
- Language
- English
- Resource Type
- Journal article
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