Development of hybrid heuristic‐assisted dynamic data auditing strategy in cloud sector

Abstract

AbstractCloud computing is performed by hosting the data of data owners on cloud servers, where the data consumers (users) are able to get the data over servers. Though, several security aspects are raised during cloud storage regarding the data availability and data integrity. On the other hand, a novel scheme of data hosting services is introduced owing to data outsourcing which also raises additional security problems. In addition, several methods are presented by taking either “identity‐based cryptography (IBC) or public key infrastructure (PKI).” Hence, a secure and effective dynamic data auditing scheme is preferable for convincing data owners to ensure precise data storage in the cloud. This paper focuses on implementing a new hybrid heuristic‐assisted strategy for managing cloud storage with the help of efficient auditing schemes. This paper tries to optimize the data structures in the cloud storage with a new improved hybrid differential evolution‐teamwork optimization algorithm (HED‐TOA) with the integration of the teamwork optimization algorithm (TOA) and differential evolution (DE) algorithms. It aims to alleviate the problems raised during the dynamic data update operations including “insert, modify, delete, and append.” This improved HED‐TOA help in performing the data auditing. This model overcomes the problem of modifications occurring in the data structure while doing the dynamic data update operations and thus, it ensures efficient data auditing and data management in cloud computing. This work considers the aim of reducing computation as well as communication costs during the data storage process in the cloud. The performance estimation demonstrates that there is considerable contrast between the traditional methods and the proposed technique in terms of the communication and computation cost on the cloud and auditor.