In approach that provides data managing authorization to


In the recent years, as
cloud computing has rapidly grown, many research efforts have been presented
that consider se-curity and privacy into the development process. Almorsy et
al. 10 introduced a Model-Driven Security Engineering at Runtime ([email protected])
approach for multi-tenant cloud-based applications. [email protected] supports different
tenants and service providers security requirements at runtime instead of
design time by externalizing security from the application. More specific,
service providers may impose some security controls as mandatory but multi
tenants can also add extra security requirements at runtime at their own
instance of the application. Fernandez et al. 11 presented a method on how to
build a cloud Security Reference Architecture (SRE). An SRE is an abstract
architecture that describes functionality without implementation details and
includes security mechanisms to the appropriate places in order to provide a
degree of security. This approach includes threat identification and uses
misuse patterns in order to describe how an attack can be performed. Through
this process, it can be verified that security patterns have been selected
correctly and have been placed properly in the cloud architecture. In 2015,
Perez et al 12 presented a data-centric authorization solution, namely
SecRBAC, in order to secure data in the cloud. SecRBC is a rule-based approach
that provides data managing authorization to CSP through roles and object
hierarchies. The authorization model uses advanced cryptographic techniques in
order to protect data from CSP misbehavior also. In 2016, Mouratidis et al.
13 extended Secure Tropos requirements engineering approach for traditional
software systems in order to enable modeling of security requirements that are
unique in cloud computing environment and to support the selection of the
appropriate cloud deployment model as well as the cloud service provider that
best satisfies security requirements of the system under consideration. In
2013, Tancock et al. 32 presented the archi-tecture of a Privacy Impact
Assessment (PIA) tool in order to identify and evaluate possible future
security and privacy risks on data stored in a cloud infrastructure. The risk
summary that derives from PIA tool takes into consideration aspects like who
the cloud provider is, what is the trust rating and what security and privacy
mechanisms are used. As threat modeling is an important aspect for developing
secure systems, Cloud Privacy Threat Modeling (CPTM) methodology 33 was
proposed in order to support the identification of possible attacks and to propose
the corresponding countermeasures for a cloud system through a number of
specific steps. However, CPTM was designed in order to support only EU data
protection directives
and as a result the methodology presented a number of
weaknesses in threat identification. Thus, A. Gholami and E. Laure 34
extended CPTM methodology in order to be complied with various legal
frameworks. As it is hard for an organization to choose the appropriate cloud
deployment type (public, private, hybrid or community), K. Beckers et al.
presented a method that can support requirements engineers to decide which
cloud deployment model best fits the privacy requirements of the system under
consideration 35. This approach is based on a threat analysis in parallel
with the privacy requirements that the system shall satisfy and some other
facts and assumptions about the environment like the number of stakeholders on
each deployment scenario and the domains that have to be outsourced into a


Despite the fact that all
these contributions develop dif-ferent kind of mechanisms or processes that
consider security and privacy issues in the context of cloud computing, most of
them present a number of limitations. Some of them are related to specific
cloud service models. [email protected] is referred to a Software as a Service service
(SaaS) model while the method for building a Security Reference Architecture is
referred to an Infrastructure as a Service (IaaS) service model. On the other
hand, most of the proposed frameworks, methods or processes in the context of
cloud computing deal exclusively with security or privacy issues or in some
cases privacy is considered as a subset of security. For instance, [email protected],
secRBAC and SecureTropos consider only security issues while the Privacy Assessment
Impact Tool (PIA), CPMT and the method for selecting the appropriate cloud
deployment model focus explicitly on privacy issues. In our previous work 8,
we presented the reasons why security and privacy have to be considered as two
different concepts but have to be examined under the same unified framework.
This framework has also been presented in our work. Nevertheless, one of the
most important issues is that most of the proposed frameworks that are based on
the idea of cloud computing integrate security and privacy controls during
implementation phase and not earlier in requirements phase. But, such practices
might create late corrections in security and privacy
requirements which means additional cost and severe delays in project delivery.

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As cloud computing is a new
and continuously developing environment, many research efforts have been
presented over the last decade that highlight the need of adopting security and
privacy mechanisms from the early stage of development life cycle.
Nevertheless, until today security and privacy in the context of cloud
computing is still performed as an ad-hoc process rather than an integrated
process in the development life cycle. As it is mentioned above, Mouratidis et
al. 13 presented a requirements engineering method in order to model cloud
security requirements at the design level but no privacy requirements have been
considered. Under these circumstances, literature presents a lack of integrated
methods that through a number of specific steps could be able to support the
parallel elicitation and analysis of cloud security and privacy requirements
from the early stage of system design. It is worth noting that a security and
privacy requirements engineering method at the design level should include
steps in order to fill the gap between analysis and implementation phase in
order to support system developers to select the appropriate technologies that
best satisfy security and privacy requirements.




In this paper, we presented
a set of security and privacy requirements engineering methods that have been
introduced by several researchers. Our research has focused on two areas: on
those methods that aim to support software engineers to design and develop
information systems hosted in traditional architectures and on those methods
that can be applied in cloud systems.


As already mentioned,
different security and privacy re-quirements engineering methods have been
introduced in the past as software engineers community agree that security and
privacy is still an integral part of the information systems design process.
Referring to traditional architectures, there are different approaches that
each method has been based on. For instance, security or privacy requirements
can be derived from the determination of security or privacy goals, from the
results of a risk analysis or from problem diagrams. Additionally, as it is
clear from the above analysis, most researchers deal with security or privacy
issues separately, a fact that can cause possible conflicts and late
reconsiderations in functional requirements.


On the other hand, cloud
computing is a more demanding structure as it introduces special
characteristics like multi-tenancy and on-demand services. Special
characteristics intro-duce new security and privacy concepts that software
engineers have to take into account during system designing and devel-oping.
However, even though cloud computing presents a rapid growth last decade, all
methods that have been presented by researchers present limitations while it is
noting the lack of integrated methods that support the elicitation and analysis
of security and privacy requirements in parallel.


The purpose of this research
is to demonstrate that in cloud computing area there is a lack of integrated
requirements engineering methods that consider security and privacy as two
different concepts that have to be examined in parallel under the same unified
framework. This study along with our previously proposed conceptual framework
8 will be the base for developing a new methodology in the cloud computing
area that will consider security and privacy under the same unified framework.


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