Cloud Security and SDLC Models

This assignment delves into the crucial topic of cloud computing security, examining key concerns such as data privacy and the complexities of multi-cloud environments. It requires students to analyze various software development life cycle (SDLC) models, comparing traditional approaches like Waterfall and V-Model with Agile methodologies in the context of deploying secure cloud solutions. Students are expected to demonstrate their understanding of both cloud security principles and the practical implications of different SDLC models for ensuring robust and reliable cloud deployments.

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Running head: SYSTEM ANALYSIS AND DESIGN
System Analysis and Design
Name of the Student
Name of the University
Author Note

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SYSTEM ANALYSIS AND DESIGN
Table of Contents
1. Introduction......................................................................................................................3
2. The Non-functional requirements of the system.............................................................3
2.1. Functionality.............................................................................................................3
2.2. Usability....................................................................................................................4
2.3. Reliability.................................................................................................................4
2.4. Performance..............................................................................................................4
2.5. Security.....................................................................................................................4
3. The Functional Requirements of the system Vs Non-functional Requirements.............5
4. The cloud based Solution: Hybrid Cloud........................................................................5
4.1. Strength of Hybrid Cloud.........................................................................................6
4.2. Weakness of Hybrid Cloud.......................................................................................7
5. SDLC Approach: Predictive or Adaptive ?....................................................................7
5.1. Predictive SDLC.......................................................................................................7
5.1.1. Pros of Using Predictive SDLC.........................................................................8
5.1.2 Cons of using Predictive SDLC..........................................................................8
5.2. Adaptive SDLC........................................................................................................9
5.2.1 Pros of using Adaptive SDLC............................................................................9
5.2.2. Cons of using the Adaptive SDLC....................................................................9
6. Conclusion.....................................................................................................................10

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7. References......................................................................................................................11

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SYSTEM ANALYSIS AND DESIGN
1. Introduction
Development of an information system in a cloud-based solution increases the affectivity
of data storage and data access. Therefore, system implementation of “My Health Record
System” in a cloud-based solution is a good decision of Headspace. The organization works for
the young and mental ill patients and are embarking on development of an information system
that would record and store the story or the condition of the patients in the very first time it is
being told. The different non-functional requirements of the system are identified in the report.
The report further discusses the chosen cloud environment for the project along with the
recommended SDLC approach that would be appropriate for the project implementation (Steele,
Min & Lo, 2012).
2. The Non-functional requirements of the system
The system’s non-functional requirements are to be identified for enhancing the system
performance. It includes the different system qualities, interfaces and the constraints that can
possible enhance the system’s performance (Chung, Nixon & Mylopoulos, 2012). The non
functional requirements associated with this project are as follows-
2.1. Functionality
Functionality of a system is a major criterion for measuring the efficiency of a system.
The main function of “My Health Record System” is storing the patients’ data to increase the
ease of access of the data. Therefore, a high throughput of the system is the major non-functional
requirement. Along with it the manageability of the system is an essential criteria to consider as
well.

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SYSTEM ANALYSIS AND DESIGN
2.2. Usability
The system is to be developed mainly for the patients and the professionals and therefore
it is essential for the system to offer high level of system usability. Therefore, it is a primary non-
functional requirement of the system. A simple user interface can increase the system’s usability
and therefore can be considered as a non-functional requirement.
2.3. Reliability
The information system to be designed will store the sensitive and confidential data of the
system and therefore it is very essential for the system to be reliable. The reliability of the system
can be increased by including a including an auto recovery option for easier data recovery
because of data loss. Therefore, maintaining the reliability of the system is a major non-
functional requirement for the system implementation.
2.4. Performance
The system’s performance is another major criterion to be considered for enhancing the
usability of the information system. Furthermore, the data availability when required is a
primary criterion to be considered for the system implementation.
2.5. Security
Considering the sensitive nature of the information that is to be stored in the information
system, it is a foremost criterion to look into the proper security of the system. This is more
essential because the organization is planning to implement the system in a cloud-based
environment, which is very vulnerable to attacks. Data integrity, which is a major non-functional
requirement of the system can be possible if the system is kept secured (Kulkarni et al., 2012).

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SYSTEM ANALYSIS AND DESIGN
Data encryption can therefore be considered as the major non-functional requirement of the
system.
3. The Functional Requirements of the system Vs Non-functional Requirements
The functional requirements that are mainly identified for the project are presence of
authentication or authorization levels, External Interfaces, Report button, considering the legal
requirements and different administrative functions. These are essential to be included in the
system in order to define the primary system functionality. The non-functional requirements
identified in the previous section if implemented properly would enhance the performance of the
system.
Security of the system is one of the major non-functional requirements of the system and
therefore it is related to the major functional requirement that is authentication. Authentication
and authorization levels are incorporated into a system for ensuring a proper security (Pearce &
Bainbridge, 2014).
Therefore it is essential for the system to incorporate all the major functional and the non-
functional requirements for maintain a smooth operation of the system.
4. The cloud based Solution: Hybrid Cloud
Considering the sensitive nature of the data, it is a primary concern to keep the data
secure. The storage of the patients data in a cloud environment although is very effective, but
there are increasing risk of data theft and data loss. The data to be stored are very sensitive and
confidential and therefore, organization should choose a cloud solution that will provide both
data security and ease of access. Considering all the criteria, it is recommended to use a hybrid

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cloud environment for this project. The hybrid cloud is chosen because the public cloud is very
vulnerable to attacks. With the increasing use of technology and data mining, the security of data
in a public cloud environment is an increasing concern (AlZain et al., 2012). Therefore, although
public cloud could have been a cost effective solution, it can be considered in this case as the
data to be stored are very sensitive. The private cloud however, does not have the security risk of
data loss or data theft as the network is much secured, but cannot be considered in this case as
the primary aim or objective of development of this system is the availability of the data to
different professionals. This would be a concern in a private cloud network as data access would
be difficult from a private cloud outside the organization (Galibus & Vissia, 2015). Private cloud
uses one dedicated network with access control mechanism and therefore the cost of
implementation of a system in private cloud is difficult as well. Therefore, the hybrid cloud
would be appropriate for this system.
4.1. Strength of Hybrid Cloud
The advantages or the strength of using the hybrid cloud environment are as follows-
1) The hybrid cloud environment is a mixture of public and private cloud environment
and therefore it is secure enough to store the confidential information of the patients (Li et al.,
2015).
2) The public zone that is present in the hybrid cloud environment can be leveraged from
a service provider and therefore it is a cost effective solution as well (Li et al., 2013).
3) The public Zone of the hybrid cloud environment provides an easier data access to the
different professionals whom the patients visit.

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4.2. Weakness of Hybrid Cloud
The major weaknesses of using a hybrid cloud solution are as follows-
1) The presence of both public and the private could environment although provides
additional benefits, the data movement in and out of the public and private zone of the cloud
environment can be targeted a hacker or an attacker to gain an access to the sensitive and the
confidential data.
2) The implementation cost of the system in a hybrid cloud environment is more than that
of the public cloud (Chen & Zhao, 2012).
Considering all the above aspects, it is recommended for Headspace to use a hybrid cloud
environment for the project.
5. SDLC Approach: Predictive or Adaptive ?
The software development life cycle is a major criterion to consider for successful
development and implementation of a software. The different phases of a software development
life cycle estimate the time and the labor that is required implement a project. The predictive and
adaptive approach of the software development life cycle is contrasting in its characteristics
(Tuteja & Dubey, 2012). Detailed description of the predictive and adaptive approach SDLC are
discussed in the following section.
5.1. Predictive SDLC
The predictive SDLC technique is a primary project management technique that is used
in predicting the timeline of the project. All the phases, deliverables and the project timeline is
pre planned in this approach and therefore it is used to estimate the project completion time. The

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project scope and requirements of the project is needed to be clear for project implementation
and therefore the project implementation using the predictive approach becomes even simpler.
The only constraint of using a Predictive SDLC is that once the project is set out for
implementation, the project modification becomes almost impossible. The pros and cons of using
a predictive SDLC are as follows-
5.1.1. Pros of Using Predictive SDLC
The advantages of using predictive SDLC approach in implementation of this project are
listed below-
1. The possibility of project completion within the set time is very high in predictive
SDLC approach. This is because the scope and the project requirements are set at the beginning
of the project. Therefore, the project follows a planned approach for the system implementation
and therefore there are very little chances of the project from drifting from the original schedule.
This is a major advantage of using a predictive SDLC approach.
2. since the project requirements remain clear throughout the project implementation
phase, it becomes easier to set or estimate a budget for the project.
5.1.2 Cons of using Predictive SDLC
There are certain disadvantages of using predictive SDLC as well. This are listed below-
1. In predictive SDLC the phases and the project schedule are generally identified at the
beginning of the project and therefore there is no scope of further improvement.
2. The predictive SDLC is basically the traditional waterfall model of project
methodology and therefore feedback back is generally absent in this approach.

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SYSTEM ANALYSIS AND DESIGN
5.2. Adaptive SDLC
Adaptive SDLC approach is different from predictive SDLC as the entire project timeline
or the life cycle is not determined at the beginning of the project. This approach is similar to the
agile project management that deals with the planning of the project deliverables before the
project implementation (Balaji & Murugaiyan, 2012). The presence of feedback path and
thorough system testing is a major advantage of this approach. The pros and cons of using
adaptive SDLC in system implementation are discussed below.
5.2.1 Pros of using Adaptive SDLC
The advantages of implementation of this project using the adaptive software
development life cycle approach are elaborated below-
1. The main advantage of using this approach is that, the project can be modified while its
implementation. This is because the entire project phases are not estimated at the beginning of
the project.
2. The thorough system testing of every phase helps in elimination of the bugs more
effectively from the system.
5.2.2. Cons of using the Adaptive SDLC
The cons of using adaptive SDLC in this project are listed below-
1. Maintaining a proper project timeline is difficult in this approach. This is because, the
project modification may require more time in execution.

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Therefore, it is recommended for Headspace to use the predictive SDLC approach in
development and implementation of the project (Mahalakshmi & Sundararajan, 2013).
6. Conclusion
Therefore, from the above discussion, it can be concluded that considering a hybrid cloud
solution will be best for implementation of this system. The report identifies the different non-
functional requirements of the system. The report further discusses the proper SDLC approach
that would be best for project implementation.

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7. References
AlZain, M. A., Pardede, E., Soh, B., & Thom, J. A. (2012, January). Cloud computing security:
from single to multi-clouds. In System Science (HICSS), 2012 45th Hawaii International
Conference on (pp. 5490-5499). IEEE.
Balaji, S., & Murugaiyan, M. S. (2012). Waterfall vs. V-Model vs. Agile: A comparative study
on SDLC. International Journal of Information Technology and Business Management,
2(1), 26-30.
Chen, D., & Zhao, H. (2012, March). Data security and privacy protection issues in cloud
computing. In Computer Science and Electronics Engineering (ICCSEE), 2012
International Conference on (Vol. 1, pp. 647-651). IEEE.
Chung, L., Nixon, B. A., Yu, E., & Mylopoulos, J. (2012). Non-functional requirements in
software engineering (Vol. 5). Springer Science & Business Media.
Galibus, T., & Vissia, H. E. R. M. (2015). Cloud storage security. Proc NSCE, 2014, 123-127.
Jain, A. K., & Nandakumar, K. (2012). Biometric Authentication: System Security and User
Privacy. IEEE Computer, 45(11), 87-92.
Kulkarni, G., Gambhir, J., Patil, T., & Dongare, A. (2012, June). A security aspects in cloud
computing. In Software Engineering and Service Science (ICSESS), 2012 IEEE 3rd
International Conference on (pp. 547-550). IEEE.
Li, J., Li, Y. K., Chen, X., Lee, P. P., & Lou, W. (2015). A hybrid cloud approach for secure
authorized deduplication. IEEE Transactions on Parallel and Distributed Systems, 26(5),
1206-1216.

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Li, Q., Wang, Z. Y., Li, W. H., Li, J., Wang, C., & Du, R. Y. (2013). Applications integration in
a hybrid cloud computing environment: Modelling and platform. Enterprise Information
Systems, 7(3), 237-271.
Mahalakshmi, M., & Sundararajan, M. (2013). Traditional SDLC Vs Scrum Methodology–A
Comparative Study. International Journal of Emerging Technology and Advanced
Engineering, 3(6), 192-196.
Pearce, C., & Bainbridge, M. (2014). A personally controlled electronic health record for
Australia. Journal of the American Medical Informatics Association, 21(4), 707-713.
Rittinghouse, J. W., & Ransome, J. F. (2016). Cloud computing: implementation, management,
and security. CRC press.
Steele, R., Min, K., & Lo, A. (2012). Personal health record architectures: technology
infrastructure implications and dependencies. Journal of the Association for Information
Science and Technology, 63(6), 1079-1091.
Tuteja, M., & Dubey, G. (2012). A research study on importance of testing and quality assurance
in software development life cycle (SDLC) models. International Journal of Soft
Computing and Engineering (IJSCE), 2(3), 251-257