Читать книгу Deep Learning Approaches to Cloud Security - Группа авторов - Страница 30

Shweta Solanki1* and Prafull Narooka2

1 MDS University Ajmer, Ajmer, India

2 Department of Computer Science, Agrawal College, Merta City, Rajasthan

^* Corresponding author: shweta.solanki01212@gmail.com

Abstract

There is a responsibility to maintain the privacy and security of data in the Cloud Computing environment. In present times, the need for privacy is increased due to frequent development in multi-tenant service based systems. As a system of growth increases, the requirement for privacy also increases. We use Deep Learning concepts to increase privacy levels. In this chapter, we understand the cloud computing concept within a Multi-Tenant Framework (MWF). In Multi-Tenant Frameworks, requirements for privacy and security concepts are developed using Deep Learning. The goal is to find privacy requirements across many factors in a Multi-Tenancy based systems using Deep Learning concepts. The services of Multi-Tenant based systems are aggregated due to the dynamic environment of Cloud Computing. Three consistencies will be maintained by privacy policies using Deep Learning. In Multi- Tenancy, a large number of users (tenants) use the same services required for privacy and security to maintain the durability and consistency of service.

Keywords: Multi-tenant, privacy, framework, privacy policy, cloud computing, single tenant, public, private