A time optimized and secured framework for efficient query retrieval in cloud environment

Abstract

Cloud computing is a subscription-based service, which provides ondemand scalable and elastic services to its customers using virtualization technology. In the real-world environment, cloud computing plays a crucial role which provides different kinds of services through the Internet to the cloud users, according to the requirements. A cloud service provider is an organization that offers IT-related resources, infrastructure and network services to other individuals and ensuring the on-going operation of the overall cloud infrastructure. Due to the distributive feature of computing, cloud environment is receiving greater interest in both academic and industry communities. Personal information can be outsourced by the cloud owners to the cloud server and made use of by the cloud user on public clouds with essential authorization. In order to get the specified outcome, users heavily rely upon the cloud information retrieval mode. Several research works have been conducted in the field of data retrieval employing a keyword dictionary and SQL-like encrypted queries. But an effective ranking of complex query creates considerable challenges. Secured data sharing between cloud servers and cloud users is one of the challenging issues for any dynamic groups in the cloud. Novel approaches need to be investigated to improve the multi-keyword query capabilities in the case of complex queries. Limited study has been done on processing and retrieving the top-k queries. Therefore, the proposed research work focuses on the issues of secure data sharing, applying searching operations and retrieving the results based on the top-k queries on dynamic groups in the cloud by performing an efficient hashing and indexing mechanism. Therefore, Cryptographic Multi-linear Data Sharing for Dynamic Group (CMDS-DG) framework is developed for data sharing among multiple cloud owners and cloud users. A Cryptographic Multi-linear Mapping is introduced for reducing the time consumed during data encryption. It is followed by assisting Segment Stature Hash Table which efficiently maps the encrypted files among cloud owners and users, thus reducing the storage overhead. A Repeat-Key-Rotate encryption algorithm is utilized for enhancing privacy and data sharing delivery ratio. Mapping key generated for each cloud user helps to increase the strength of maintaining the privacy details. Thus, cloud data sharing can be done with high privacy and minimum storage overhead among various cloud owners and users. For efficient data sharing, query ranking among various cloud services in a cloud environment is essential and it is achieved by Weighted Fuzzy Multi-Keyword Rank Query (WFM-KRQ) method. Here, the association of multi-keyword user query with the fuzzy rule is carried out, followed by the application of a weighted distribution function for determining and#945;-level multikeyword which help in handling the complex query. It also utilizes pruning technique to improve query retrieval rate which depends on a threshold value. With the help of the Repeat-Key-Rotate algorithm, the data are effectively shared by attaining higher query retrieval rate at minimum computational complexity on cloud user data. newline