DOTNET PROJECT
CLASS: Cloud Log
Assuring Soundness and Secrecy Scheme for Cloud Forensics
Abstract:
User
activity logs can be a valuable source of information in cloud forensic
investigations; hence, ensuring the reliability and integrity of such logs is
crucial. Most existing solutions for secure logging are designed for
conventional systems rather than the complexity of a cloud environment. In this
paper, we propose the Cloud Log Assuring Soundness and Secrecy (CLASS) process
as an alternative scheme for the securing of logs in a cloud environment. In
CLASS, logs are encrypted using the individual user's public key so that only
the user is able to decrypt the content. In order to prevent unauthorized
modification of the log, we generate proof of past log (PPL) using Rabin's
fingerprint and Bloom filter. Such an approach reduces verification time significantly.
Findings from our experiments deploying CLASS in OpenStack demonstrate the
utility of CLASS in a real-world context.
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