An Enhancement of approaches for securing and sharing of bigdata in cloud server

Abstract

The increasing trend of using information resources and the advances of data processing tools lead to extend usage of big data. The extensive uses of big data bring different challenges; among them are data analysis, treatment and conversion, searching, storage, visualization, security, and privacy.Big data security and privacy are potential challenges in cloud computing environment as the growing usage of big data leads to new data threats, particularly when dealing with sensitive and critical data such as trade secrets, personal and financial information. Any loss that could happen to this data may negatively affect the organization s confidence and might damage their reputation. Moreover, moving big data within different clouds that have different levels of sensitivity might expose important data to threats. newlineIn the first contribution, is proposed for large information stockpiling in cloud server has been created to deal with and secure the enormous information put away in the cloud server. The main goal of this method is to effectively update and verify the access policies to improve the flexibility in authorizations and thereby improving the resource usability and business timeliness. In this scheme, Improved N-th degree Truncated polynomial Ring Units (INTRU) and Attribute Based Access Control (ABAC) schemes are combined to improve the efficiency of security strength in cloud server and provide efficient access policies enforced access decisions without adding any permission. newlineIn the second contribution, Spatio temporal Constrained Secure Scheme with Deep learning-based Anomaly Detection System (SCSS-DADS) is proposed to prevent and secure big data stored in the cloud servers. newline