Efficient privacy preserving data sanitization over cloud using optimal algorithms

Abstract

Cloud computing (CC) is a complex infrastructure of software,hardware, processing and storage that are available as a service. CC has been envisioned as the next-generation architecture for IT enterprise. While most of the CC offerings might appear enticing, there remain issues of reliability,portability, privacy, and security. The complete benefits of CC can be experienced when acknowledging and solving the real privacy and security concerns those are come along with storing sensitive and personal information in databases and software scattered around the Internet. One of the main concerns in CC is privacy-preserving, which is the process of covering up personal or sensitive data related to a single user from other users and parties. In cloud computing, the privacy of data stored is very much desirable as the data can be of any information related to the identity of a user. The leakage or violation of any such privacy might cause the major failure of the system. The proper safeguards have to be taken to prevent unauthorized users from accessing data, disclose, copy, use or modify any of the personal information. As there is no standard approach for CC security, third-party arrangements can be utilized. Data sanitization is a crucial part of privacy-preserving in cloud computing. Data sanitization removes some part of data from the original resource subsequently it was offered for other users. The most important step in the sanitization approach is to guarantee that the data was removed from the cloud service provider. When all the files are sanitized and all possibilities of embedded threats are eliminated, every file-based threat will be disarmed by data sanitization without the requirement of the detection process. When the implementation of data sanitization is poor, then there is a chance for data loss. Here, the data sanitization approach for privacy preserving in the cloud has been presented. newline