Edge Computing and Blockchain-Based Distributed Audit of Outsourced Dynamic Data

Abstract

Dynamic outsourced data managed by an untrusted third party is prone to integrity violation. Data auditing is a well-known posterior mechanism to detect integrity violations. Existing integrity auditing schemes are centralized and take significant computation, storage, or communication cost at the data owner. Recently, a distributed auditing scheme involving three parties: the data owner, storage server, and end-users, is proposed. However, it uses redundant failure reports for a corrupt file increases the storage, computation, and communication costs. Also, the low-configured end-users may avoid auditing tasks for efficiency reasons. This paper proposes a secure and efficient distributed auditing scheme for outsourced data that utilizes blockchain and edge computing. The blockchain securely stores distinct failure reports, while edge nodes handle local auditing tasks. The scheme is compared with the existing distributed auditing scheme and found to be secure, and more efficient in terms of computational cost at the data owner and communication cost used by the scheme participants.