BCFL Logging
: an approach to acquire and preserve admissible digital forensics evidence in the cloud ecosystem

  • Kenny Awuson - David

    Student thesis: Doctoral ThesisDoctor of Philosophy


    The on-demand nature of cloud computing technology has altered the way data and information are shared and handled online. However, organisations that continue to leverage the benefits of cloud on-demand services face severe incremental security challenges. In addition, there are well-known security, privacy and trust issues among the cloud computing stakeholders that need to be solved. These drawbacks are particularly problematic, and cloud stakeholders have struggled to solve these challenges or establish trustworthiness in the cloud environment. A novel, permissioned Blockchain Cloud Forensic Logging (BCFL) framework approach is needed, to be applied in the cloud to establish trust, traceability and admissible log evidence. Blockchain is a peer-to-peer
    network that uses a decentralised Distributed Ledger Technology (DLT) with a smart contract that maintains a tamper-resistant transaction ledger. It provides a promising solution for a cloud forensics acquisition. This research has designed and implemented a Blockchain Cloud Forensic Logging (BCFL) framework using the Design Science Research Methodological (DSRM) approach. BCFL operates primarily in four stages: (1) Process transaction logs using Blockchain distributed ledger technology (DLT). (2) Use a Blockchain smart contract to maintain the integrity of logs and establish a transparent chain of custody. (3) Validate all transaction logs. (4) Maintain transaction log immutability. The results from the single case study demonstrate that BCFL will mitigate the challenges and complexities faced by digital forensics investigators in acquiring admissible digital evidence from the cloud ecosystem. In addition, an instantaneous performance monitoring of the Blockchain cloud forensic logging framework was evaluated. BCFL will ensure trustworthiness, integrity, authenticity and non-repudiation of the log evidence in the cloud.
    Date of AwardJan 2022
    Original languageEnglish
    Awarding Institution
    • Coventry University
    SupervisorNorlaily Yaacob (Supervisor) & Nazaraf Shah (Supervisor)


    • Admissibility
    • Blockchain
    • Cloud Forensics
    • Design Science Methodology
    • Digital log evidence
    • GDPR
    • Hyperledger Fabric
    • Trustworthiness

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