Dynamic Big Data Storage using Efficient Auditing Protocol With Full-Grained Updates
Big data is an evolving term that describes any voluminous amount of structured, semi-structured and unstructured data. The term is often used when speaking about peta-bytes and exa-bytes of data. The security and privacy is the static and huge challenging issue in big data storage. There are many ways to compromise data because of insufficient authentication, authorization, and audit (AAA) controls, such as deletion or alteration of records without a backup of the original content. The existing research work showed that it can fully support authorized auditing and fine-grained update requests. However, such schemes in existence suffer from several common drawbacks. First maintaining the storages can be a difficult task and second it requires high resource costs for the implementation. This paper, Propose a formal analysis technique called full grained updates. It includes the efficient searching for downloading the uploaded file and also focuses on designing the auditing protocol to improve the server-side protection for the efficient data confidentiality and data availability.
Conference Name: Third National Conference on Networking and Communication Systems
Conference Date: 13, February 2015
Paper ID: ncs05