Deep Learning Approaches to Cloud Security. Группа авторов

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      Privacy in Multi-Tenancy Cloud Using Deep Learning

       Shweta Solanki1* and Prafull Narooka2

       1 MDS University Ajmer, Ajmer, India

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

      ^* Corresponding author: [email protected]

       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

2.1 Introduction

It is very important to understand the need for Multi-Tenancy in the Cloud Computing environment because today all work is done with the help of an internet transaction mode. In this environment, the database and schema used in the database change or modify frequently. Data is stored in different areas in different databases [1]. The cloud computing environment of every organisation is different. The real need of cloud environment-like private or public modes depends on the concept of data and tenant needs, organisation needs, or the configuration of a database depending on the structure of the database and the model used by the organisation for privacy policies. The security level of the Multi-Tenancy structure should maintain the durability of an application to maintain consistency of the system and avoid interruption of the regular based work done by the tenant. The concept of Multi-Tenancy in multiple databases requires more privacy between tenants both logically and physically to accommodate a greater the need for privacy and security in each work area. Using Deep Learning concepts can improve the complexity in accessing and managing a database. Using Deep Learning concepts should reduce access and increase efficiency, preventing the leak of data, hacking, or other risks because they can be found out easily and improve the quality of Multi-Tenant system efficiency. So, in Deep Learning, the privacy concept is improved and the transparency between the multiple tenants increases, maintaining privacy. Deep Learning concepts are very powerful and scalable for implementing. In Deep Learning, databases are managed efficiently. The Deep Learning algorithm makes this affordable. The Deep Learning concept has the ability to improve data driven predictions. It finds the patterns of privacy and security in databases in Multi-Tenancy. This can provide good or better values for organisation. In Deep Learning, the work is done for binary, category, and value predictions in Cloud Computing. In this chapter, we discuss the basic concept of Multi-Tenancy, privacy requirements, and the Cloud Computing concept with Deep Learning.

2.2 Basic Structure

It is very important to understand Cloud Computing, as it provides service accordingly to its user end. Whether it is a private or public cloud depends the requirement of user, like Multi-Tenancy or Single Tenancy. It is also an on demand service that depends on tenant requirement, resource availability, storage requirement, activity management, and which topology is required for the distributed system. The tenant requires either a centralised or decentralised framework. Security in Cloud Computing also depends on the concept of the database and the need for bigness and organisation. As the need arises, the organisation selects the structure of Cloud Computing. Then, they create the schema and select a data model and select a Single or Multi-Tenancy concept for work. Complexity and cost are also dependent on the requirements of the organisation’s needs. There are structures of Cloud Computing and the Multi-Tenancy concept available illustrating the impact of Multi-Tenancy in Cloud Computing. The cloud manages the concept of Multi-Tenancy, shares resources, and manages services with many tenants. Management and the utility services are provided by the structure according to need. This section discusses the basic structure of Cloud Computing and how the work is done in combination with Multi-Tenancy [2].

      2.2.1 Basic Structure of Cloud Computing

      Cloud Computing services are used by every service area, whether the business is small or large.

      The cloud facility is available according to the requirements of the business. The cloud enables the facility to store data, whether it be large or small, and provides access to data from any location and any hardware or a virtual environments for accessing or storing data.

      Cloud Computing provides the services of both service oriented and event driven architecture.

The given diagram represents the various services of the cloud. All services are inter-related to each other. The three main parties involved are the cloud service consumer, cloud service provider, and cloud broker shown in Figure 2.1.