Authors: Aditya Agrawal, Abhishek, Yash Ranjan Bhargav
Abstract: The rapid adoption of multi-cloud and serverless architectures has fundamentally altered how digital evidence is generated, distributed, and lost, creating significant challenges for contemporary digital forensic investigations. Current cloud forensic practices remain largely provider-specific and assume stable infrastructure, leaving investigators without reliable mechanisms to detect, preserve, and correlate volatile forensic artifacts across decentralized cloud environments. As a result, critical evidence such as execution logs, transient identifiers, and ephemeral state information is frequently incomplete, inconsistent, or legally fragile. This paper presents a provider-agnostic forensic framework designed to support systematic detection, acquisition, and preservation of digital evidence in multi-cloud and serverless deployments. The proposed approach introduces a canonical event model, cross-provider log normalization, and a coordinated snapshotting strategy to capture transient artifacts while maintaining evidentiary integrity and provenance. Event correlation is achieved through time-aligned stitching of heterogeneous logs, enabling accurate reconstruction of distributed execution timelines. A prototype implementation was evaluated across simulated multi-cloud environments incorporating serverless workloads from multiple providers. Experimental results demonstrate improved evidence completeness and correlation accuracy compared to baseline cloud-native acquisition methods, while introducing minimal operational overhead. The findings indicate that standardized, cross-cloud forensic mechanisms are both feasible and necessary, offering practical guidance for investigators and cloud service consumers seeking legally defensible forensic readiness in decentralized cloud infrastructures.
International Journal of Science, Engineering and Technology