Improvement of Data Integrity and Data Dynamics for Data Storage Security in Cloud Computing

Abstract

Cloud stands today as an emerging standard, however, data outsourcing paradigm is main security concern in cloud. To make sure that the data stored on the cloud is safe, frequent data integrity checking is imperative. This work considers the problem of data integrity in cloud storage and makes use of Dynamic Merkle Hash Tree (DMHT) along with AES and SHA-1 algorithms to solve the same. RSA algorithm has been used by many previously developed systems; the proposed work makes use of AES which leads to performance improvement. The work also makes use of the concept of Third Party Auditor (TPA) to achieve Public Auditing. In case of corruption of data or data loss, the proposed work promises to recover the lost data with the help of a backup system. In order to support dynamic data operations, the Merkle Tree is made dynamic by making use of relative index. Further, to save the communication bandwidth and cost, block level recovery is made instead of recovery of entire file. On comparison with previous systems, the proposed system shows reduction in server computation time. The proposed work thus aims at improving and maintaining data integrity at untrusted server, supports dynamic data operations and makes recovery possible by providing a recovery system.