A Framework for Data Integrity Checking In Cloud Computing

Abstract

Cloud computing has emerged as a utility computing paradigm that offers great potential for storing data remotely. It efficiently reduces data maintenance pressures of an organization. However, preserving data integrity and resolving security concerns of outsourced data still remains to be a challenge for data owners, due to loss of control over data. Thus, integrity checking of outsourced data in cloud computing environments becomes crucial for identifying loss of data or any corruption incident in timely manner. Data integrity checking significantly reduces the impact of risks caused due to such losses. In recent years, because of the growing trends of outsourcing data, significant progress has been made by researchers for designing efficient data integrity checking schemes. Most of the existing solutions have not been able to achieve the desired requirements of integrity checking schemes like public auditing of dynamic data, unlimited times of integrity checking and providing data freshness guarantees etc. Moreover, less attention had been given to minimize computation overhead incurred in integrity verification. Hence, new data integrity checking schemes for cloud computing are needed that fulfill the desired requirements and are computationally efficient Addressing the issue of integrity checking of outsourced data through literature survey, a comparative analysis of existing data integrity checking schemes is presented in the thesis. Detailed review of cryptographic and mathematical methods used to devise data integrity checking schemes has been carried out. A specific analysis based on security methods, storage overhead, computation cost and communication cost is presented in tabular form. Further, a comprehensive view of desirable properties of these schemes is presented. The challenges in the composition of an efficient data integrity checking scheme for cloud computing environment have been highlighted.