Data Integrity Audit Based on Data Blinding for Cloud and Fog Environment

Cloud-fog computing represents a pioneering computing paradigm that extends the capabilities of traditional cloud computing by leveraging fog nodes to deliver diverse services. Conventional data integrity auditing faces challenges such as inadequate data security, sluggish data processing speeds, and suboptimal communication efficiency. To address these issues, this paper introduces a data integrity audit scheme founded on data blinding. In this approach, edge devices within the transmission node establish a fog computing layer between the cloud service provider and the data owner, mitigating transmission delays. The dynamic allocation of subordinate distribution relationships and weights among fog nodes optimizes data paths, further reducing transmission delays. Additionally, a blind factor is incorporated into the integrity audit during evidence generation to prevent potential data leaks. The paper presents a security model and security proof based on computational Diffie-Hellman (CDH) assumptions. Experimental results demonstrate that the integration of the fog computing layer and blind factor into the data integrity audit process significantly reduces data communication delays while enhancing overall data audit security.

Keywords — Cloud and fog computing, data blinding, integrity audit, cloud storage.