An Improved Secure Public Cloud Auditing Scheme in Edge Computing

Abstract

Cloud storage plays an important role in the data processing of edge computing. It is very necessary to protect the integrity of these data and the privacy of users. Recently, a cloud auditing scheme which can be used to smart cities has been proposed, which is lightweight and privacy-preserving. Although this scheme has very good performance and is a very valuable work, we find that there is insecurity in it. By giving two kinds of attacks, we prove that a malicious cloud server provider (CSP) can forge auditing proof and can successfully pass the verification of the third-party auditor (TPA) even if the CSP deletes the user’s data. Then, based on this scheme, we propose an improved scheme, which can resist the forgery attack from malicious CSP. Through security analysis, our scheme improves the security compared to the original scheme without reducing the efficiency.

Effective privacy preserving in cloud computing using position aware Merkle tree model

“…The other developed model was efficient for novel auditing methods, in providing security to data in the cloud storage based on convergence and to perform symmetric encryption. However, the model issued data that was lost with the cloud where the data loss process occurred in the infrastructure irrespective of the measures provided by the cloud service providers (CSPs) [13]. Shabbir et al [14] utilized data integrity verification based on the short signature algorithm that provided privacy protection.…”