Implementing a Secure Web Database in a Cloud Instance

This report discusses the steps to implement a secure web database in a cloud instance using a conceptual design of a players and sessions database as an example. It covers the creation of a cloud SQL instance, setting up a MySQL client for database creation and management, and the security issues related to cloud-based web databases.

Title Page
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Table of Contents
Introduction......................................................................................................................................3
How to Implement a Web Database in a Cloud Instance................................................................3
Security Issues.................................................................................................................................5
Conclusion.......................................................................................................................................6
References........................................................................................................................................7
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Introduction
The aim of the report is to discuss how to implement a secure web database in a cloud instance.
There is the conceptual design of a players and sessions database that has been taken as an
example.
How to Implement a Web Database in a Cloud Instance
Implementation of a web database on a cloud instance is similar to the implementation of a
regular database implemented over SQL, MySQL and Oracle etc. The steps are,
 First, it needs to be translated into a suitable logical schema and physical schema.
 Following that, it needs to select a cloud computing platform, like Google and the
database development platform, like MySQL (Rajan, 2018).
 It is assumed that the user already has subscribed for the database development platform
and has all necessary login details.
 Then it needs to create a Cloud SQL instance. For Google Cloud and MySQL database, it
will require to go the cloud SQL instance page, then clicking on create an instance, select
MySQL, and click next (Rajan, 2018).
 To implement a database that follows the current technologies, it needs to select the
second generation.
 Then a name should be given to the database and a password must be set for the admin
account or the 'root'@'%' user.
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 Then it will require to set a region for the database. And the system will place the
instance on that region where the database will be able to access the resources. There is
no need to select a zone (Rajan, 2018).
 Then it will ask for the configuration. The configuration must be done for the parameters
like the database version, machine type, storage type, storage capacity, whether automatic
storage increase is needed or not, the limit to automatic storage increase, and backup
solutions. The parameters for backup solutions include high availability, automated
backups, binary logging and authorisation of networks. It also needs to set database flags,
setting maintenance window and maintenance timing.
 After setting all these parameters, it needs to create a database instance by clicking on
‘Create’.
Once the instance is created, it needs to set up a MySQL client for the creation and management
of the database. So, the steps are,
 Select an already created cloud SQL instance from the instance page.
 Click on the database tab.
 Then create a database by clicking on the ‘Create Database’. A dialog box will open. It
needs to give the name of the database there. Other than that, optionally a user can set
options for collation and the character set.
Once the database is created, it needs a listing of the database. The steps are,
 Again from the Google Cloud Platform console, it needs to go to the instance page and
select the instance for which the database will be listed.
 A user can list a database by clicking on Databases.
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To add the tables, attributes, and values in a selected database, it needs to follow the MySQL
commands and queries like any other MySQL database. In this case, it will need to create all
three tables with respective attributes, primary and foreign keys etc. Then it will require to
populate the database with suitable data in the tables.
Security Issues
Cloud computing has made the web-based database implementation more convenient and
simpler than an implementation of the same database management system in a traditional process
(Lakshmanan, 2017). However, there are various security concerns. Some of those are given
here.
 The overall safety of the storage of data on a cloud-based web database.
 Database as a Service provider may be able to access private and sensitive data of the
consumers (Chao, 2012).
 It is not possible to locate or understand the actual physical location of the actual data and
the backup data (Lehner & Sattler, 2013).
 It may allow external users to access data from the database of the user.
 It must follow all regulatory compliances related to DBaaS (Udoh, 2012).
 There may be hidden and sensitive data and that have the chances of unauthorised access
from a possible data threat of unauthorised access to data (Udoh, 2012).
 There are risks of performance attacks and DDoS attacks
 There are high risks of SQL injection attacks (Hameurlain, Rahayu, & Taniar, 2013)
 Authorised users may get involved in data theft activities (Hameurlain et al., 2013).
 It may allow a neighbouring tenant to access data in a poorly secured multi-tenant
database system (Udoh, 2012).
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Conclusion
In this report, the details of how the web implementation of a database can be done has been
discussed in details. It covers the steps and details of creating an instance of populating data in
the newly created database system.
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References
Chao, L. (2012). Cloud Computing for Teaching and Learning: Strategies for Design and
Implementation: Strategies for Design and Implementation: Information Science
Reference.
Hameurlain, A., Rahayu, W., & Taniar, D. (2013). Data Management in Cloud, Grid and P2P
Systems: 6th International Conference, Globe 2013, Prague, Czech Republic, August 28-
29, 2013, Proceedings: Springer Berlin Heidelberg.
Lakshmanan, V. (2017). Data Science on the Google Cloud Platform: Implementing End-to-End
Real-Time Data Pipelines: From Ingest to Machine Learning: O'Reilly Media.
Lehner, W., & Sattler, K. U. (2013). Web-Scale Data Management for the Cloud: Springer New
York.
Rajan, L. (2018). Google Cloud Platform Cookbook: Implement, deploy, maintain, and migrate
applications on Google Cloud Platform: Packt Publishing.
Udoh, E. (2012). Applications and Developments in Grid, Cloud, and High-Performance
Computing: Information Science Reference.
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