Abstract
In this paper, we proposed the blockchain-assisted shared audit framework (BSAF) to analyze digital forensic data in the IoT platform. The proposed framework was designed to detect the source/cause of data scavenging attacks in virtualized resources (VR). The proposed framework implements blockchain technology for access log and control management. Access log information is analyzed for its consistency of adversary event detection using logistic regression (LR) machine learning and cross-validation. An adversary event detected by LR is filtered using cross-validation to retain the precision of data analysis for varying user density and VRs. Experimental results prove the consistency of the proposed method by improving the data analysis, as well as reducing analysis time and the adversary event rate.
•The BSAF has been proposed for analyzing digital forensic data in IoT platform.•It is designed for detecting data scavenging attacks in virtualized resources (VRs).•It assimilates blockchain technology for access log and control management.•It is analyzed for adversary event detection using logistic regression (LR).•It is filtered using cross-validation for retaining the precision of data analysis.