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Supported by Core Electronic Device, High General Chip and
Basic Software program of China: 2011ZX01043-001-001
Supported by National Natural Science Foundation of China:
60803131
Supported by Electronic Information Industry Development Fund
Project: "Multi-industries oriented Information Technology Services
Knowledge Base System Development."
Supported by National basic research program of China (973):
2012CB724107
Data Security and Privacy Protection Issues in
Cloud Computing
Deyan Chen
1
College of Information Science and Engineering
Northeastern University
1
Shenyang, China
Email:chendeyan@neusoft.com
Hong Zhao
1,2
Academy
Neusoft Corporation
2
Shenyang, China
Abstract—It is well-known that cloud computing has many
potential advantages and many enterprise applications and data
are migrating to public or hybrid cloud. But regarding some
business-critical applications, the organizations, especially large
enterprises, still wouldn’t move them to cloud. The market size
the cloud computing shared is still far behind the one expected.
From the consumers’ perspective, cloud computing security
concerns, especially data security and privacy protection issues,
remain the primary inhibitor for adoption of cloud computing
services. This paper provides a concise but all-round analysis on
data security and privacy protection issues associated with cloud
computing across all stages of data life cycle. Then this paper
discusses some current solutions. Finally, this paper describes
future research work about data security and privacy protection
issues in cloud.
Keywords-access control; cloud computing; cloud computing
security; data segregation; data security; privacy protection.
I. INTRODUCTION
From initial concept building to current actual deployment,
cloud computing is growing more and more mature. Nowadays
many organizations, especially Small and Medium Business
(SMB) enterprises, are increasingly realizing the benefits by
putting their applications and data into the cloud. The adoption
of cloud computing may lead to gains in efficiency and
effectiveness in developing and deployment and save the cost
in purchasing and maintaining the infrastructure.
Regarding definition of cloud computing model, the most
widely used one is made by NIST as “Cloud computing is a
model for enabling convenient, on-demand network access to a
shared pool of configurable computing resources (e.g.,
networks, servers, storage, applications, and services) that can
be rapidly provisioned and released with minimal management
effort or service provider interaction. This cloud model
promotes availability and is composed of five essential
characteristics, three service models, and four deployment
models.”[1] The cloud computing model NIST defined has
three service models and four deployment models. The three
service models, also called SPI model, are: Cloud Software as a
Service (SaaS), Cloud Platform as a Service (PaaS) and Cloud
Infrastructure as a Service (IaaS). The four deployment models
are: Private cloud, Community cloud, Public cloud and Hybrid
cloud.
Compared with the traditional IT model, the cloud
computing has many potential advantages. But from the
consumers’ perspective, cloud computing security concerns
remain a major barrier for the adoption of cloud computing.
According to a survey from IDCI in 2009, 74% IT managers
and CIOs believed that the primary challenge that hinders them
from using cloud computing services is cloud computing
security issues [2]. Another survey carried out by Garter in
2009, more than 70% CTOs believed that the primary reason
not to use cloud computing services is that there are data
security and privacy concerns.
Although cloud computing service providers touted the
security and reliability of their services, actual deployment of
cloud computing services is not as safe and reliable as they
claim. In 2009, the major cloud computing vendors
successively appeared several accidents. Amazon's Simple
Storage Service was interrupted twice in February and July
2009. This accident resulted in some network sites relying on a
single type of storage service were forced to a standstill. In
March 2009, security vulnerabilities in Google Docs even led
to serious leakage of user private information. Google Gmail
also appeared a global failure up to 4 hours. It was exposed that
there was serious security vulnerability in VMware
virtualization software for Mac version in May 2009. People
with ulterior motives can take advantage of the vulnerability in
the Windows virtual machine on the host Mac to execute
malicious code. Microsoft's Azure cloud computing platform
also took place a serious outage accident for about 22 hours.
Serious security incidents even lead to collapse of cloud
computing vendors. As administrators’ misuse leading to loss
of 45% user data, cloud storage vendor LinkUp had been
forced to close.
Security control measures in cloud are similar to ones in
traditional IT environment. As multi-tenant characteristic,
service delivery models and deploy models of cloud computing,
2012 International Conference on Computer Science and Electronics Engineering
978-0-7695-4647-6/12 $26.00 © 2012 IEEE
DOI 10.1109/ICCSEE.2012.193
647
compared with the traditional IT environment, however, cloud
computing may face different risks and challenges.
Traditional security issues are still present in cloud
computing environments. But as enterprise boundaries have
been extended to the cloud, traditional security mechanisms are
no longer suitable for applications and data in cloud. Due to the
openness and multi-tenant characteristic of the cloud, cloud
computing is bringing tremendous impact on information
security field:
(1) Due to dynamic scalability, service abstraction, and
location transparency features of cloud computing models, all
kinds of applications and data on the cloud platform have no
fixed infrastructure and security boundaries. In the event of
security breach, it’s difficult to isolate a particular physical
resource that has a threat or has been compromised.
(2) According to the service delivery models of cloud
computing, resources cloud services based on may be owned
by multiple providers. As there is a conflict of interest, it is
difficult to deploy a unified security measures;
(3) As the openness of cloud and sharing virtualized
resources by multi-tenant, user data may be accessed by other
unauthorized users.
(4) As the cloud platform has to deal with massive
information storage and to deliver a fast access, cloud security
measures have to meet the need of massive information
processing.
This paper describes data security and privacy protection
issues in cloud. This paper is organized as follows: Section II
gives a brief description of what exactly cloud computing
security-related issues are. Section III discusses data security
and privacy protection issues associated with cloud computing
across all stages of data life cycle. Section IV shows current
solutions for data security and privacy protection issues in
cloud. Section V summarizes the contents of this paper. Section
VI describes future research work.
II. C
LOUD COMPUTING SECURITY ISSUSES
A. Cloud Computing Security
Wikipedia [3] defines Cloud Computing Security as “Cloud
computing security (sometimes referred to simply as "cloud
security") is an evolving sub-domain of computer security,
network security, and, more broadly, information security. It
refers to a broad set of policies, technologies, and controls
deployed to protect data, applications, and the associated
infrastructure of cloud computing.” Note that cloud computing
security referred to here is not cloud-based security software
products such as cloud-based anti-virus, anti-spam, anti-DDoS,
and so on.
B. Security Issues Associated with the Cloud
There are many security issues associated with cloud
computing and they can be grouped into any number of
dimensions.
According to Gartner [4], before making a choice of cloud
vendors, users should ask the vendors for seven specific safety
issues: Privileged user access, regulatory compliance, data
location, data segregation, recovery, investigative support and
long-term viability. In 2009, Forrester Research Inc. [5]
evaluated security and privacy practices of some of the leading
cloud providers (such as Salesforce.com, Amazon, Google, and
Microsoft) in three major aspects: Security and privacy,
compliance, and legal and contractual issues. Cloud Security
Alliance (CSA) [6] is gathering solution providers, non-profits
and individuals to enter into discussion about the current and
future best practices for information assurance in the cloud.
The CSA has identified thirteen domains of concerns on cloud
computing security [7].
S. Subashini and V. Kavitha made an investigation of cloud
computing security issues from the cloud computing service
delivery models (SPI model) and give a detailed analysis and
assessment method description for each security issue [8].
Mohamed Al Morsy, John Grundy and Ingo Müller explored
the cloud computing security issues from different perspectives,
including security issues associated with cloud computing
architecture, service delivery models, cloud characteristics and
cloud stakeholders [9]. Yanpei Chen, Vern Paxson and Randy
H. Katz believed that two aspects are to some degree new and
essential to cloud: the complexities of multi-party trust
considerations, and the ensuing need for mutual auditability.
They also point out some new opportunities in cloud
computing security [10].
According to the SPI service delivery models, deployment
models and essential characteristics of cloud, there are security
issues in all aspects of the infrastructure including network
level, host level and application level.
Figure 1. Cloud computing security architecture
III. DATA SECURITY AND PRIVACY PROTECTION ISSUES
The content of data security and privacy protection in cloud
is similar to that of traditional data security and privacy
protection. It is also involved in every stage of the data life
cycle. But because of openness and multi-tenant characteristic
of the cloud, the content of data security and privacy protection
in cloud has its particularities.
The concept of privacy is very different in different
countries, cultures or jurisdictions. The definition adopted by
Organization for Economic Cooperation and Development
(OECD) [11] is "any information relating to an identified or
648
identifiable individual (data subject)." Another popular
definition provided by the American Institute of Certified
Public Accountants (AICPA) and the Canadian Institute of
Chartered Accountants (CICA) in the Generally Accepted
Privacy Principles (GAPP) standard is “The rights and
obligations of individuals and organizations with respect to the
collection, use, retention, and disclosure of personal
information.” Generally speaking, privacy is associated with
the collection, use, disclosure, storage, and destruction of
personal data (or personally identifiable information, PII).
Identification of private information depends on the specific
application scenario and the law, and is the primary task of
privacy protection.
The next several sections analyze data security and privacy
protection issues in cloud around the data life cycle.
A. Data Life Cycle
Data life cycle refers to the entire process from generation
to destruction of the data. The data life cycle is divided into
seven stages. See the figure below:
Figure 2. Data life cycle
B. Data Generation
Data generation is involved in the data ownership. In the
traditional IT environment, usually users or organizations own
and manage the data. But if data is to be migrated into cloud, it
should be considered that how to maintain the data ownership.
For personal private information, data owners are entitled to
know what personal information being collected, and in some
cases, to stop the collection and use of personal information.
C. Transfer
Within the enterprise boundaries, data transmission usually
does not require encryption, or just have a simple data
encryption measure. For data transmission across enterprise
boundaries, both data confidentiality and integrity should be
ensured in order to prevent data from being tapped and
tampered with by unauthorized users. In other words, only the
data encryption is not enough. Data integrity is also needed to
be ensured. Therefore it should ensure that transport protocols
provide both confidentiality and integrity.
Confidentiality and integrity of data transmission need to
ensure not only between enterprise storage and cloud storage
but also between different cloud storage services. In other
words, confidentiality and integrity of the entire transfer
process of data should be ensured.
D. Use
For the static data using a simple storage service, such as
Amazon S3, data encryption is feasible. However, for the static
data used by cloud-based applications in PaaS or SaaS model,
data encryption in many cases is not feasible. Because data
encryption will lead to problems of indexing and query, the
static data used by Cloud-based applications is generally not
encrypted. Not only in cloud, but also in traditional IT
environment, the data being treated is almost not encrypted for
any program to deal with. Due to the multi-tenant feature of
cloud computing models, the data being processed by cloud-
based applications is stored together with the data of other
users. Unencrypted data in the process is a serious threat to data
security.
Regarding the use of private data, situations are more
complicated. The owners of private data need to focus on and
ensure whether the use of personal information is consistent
with the purposes of information collection and whether
personal information is being shared with third parties, for
example, cloud service providers.
E. Share
Data sharing is expanding the use range of the data and
renders data permissions more complex. The data owners can
authorize the data access to one party, and in turn the party can
further share the data to another party without the consent of
the data owners. Therefore, during data sharing, especially
when shared with a third party, the data owners need to
consider whether the third party continues to maintain the
original protection measures and usage restrictions.
Regarding sharing of private data, in addition to
authorization of data, sharing granularity (all the data or partial
data) and data transformation are also need to be concerned
about. The sharing granularity depends on the sharing policy
and the division granularity of content. The data transformation
refers to isolating sensitive information from the original data.
This operation makes the data is not relevant with the data
owners.
F. Storage
The data in the cloud may be divided into: (1) The data in
IaaS environment, such as Amazon's Simple Storage Service;
(2) The data in PaaS or SaaS environment related to cloud-
based applications.
The data stored in the cloud storages is similar with the
ones stored in other places and needs to consider three aspects
of information security: confidentiality, integrity and
availability.
The common solution for data confidentiality is data
encryption. In order to ensure the effective of encryption, there
needs to consider the use of both encryption algorithm and key
strength. As the cloud computing environment involving large
amounts of data transmission, storage and handling, there also
needs to consider processing speed and computational
649
efficiency of encrypting large amounts of data. In this case, for
example, symmetric encryption algorithm is more suitable than
asymmetric encryption algorithm.
Another key problem about data encryption is key
management. Is who responsible for key management? Ideally,
it’s the data owners. But at present, because the users have not
enough expertise to manage the keys, they usually entrust the
key management to the cloud providers. As the cloud providers
need to maintain keys for a large number of users, key
management will become more complex and difficult.
In addition to data confidentiality, there also needs to be
concerned about data integrity. When the users put several GB
(or more) data into the cloud storage, they how to check the
integrity of the data? As rapid elasticity feature of cloud
computing resources, the users don’t know where their data is
being stored. To migrate out of or into the cloud storage will
consume the user's network utilization (bandwidth) and an
amount of time. And some cloud providers, such as Amazon,
will require users to pay transfer fees. How to directly verify
the integrity of data in cloud storage without having to first
download the data and then upload the data is a great challenge.
As the data is dynamic in cloud storage, the traditional
technologies to ensure data integrity may not be effective.
In the traditional IT environment, the main threat of the
data availability comes from external attacks. In the cloud,
however, in addition to external attacks, there are several other
areas that will threat the data availability: (1) The availability
of cloud computing services; (2) Whether the cloud providers
would continue to operate in the future? (3) Whether the cloud
storage services provide backup?
G. Archival
Archiving for data focuses on the storage media, whether
to provide off-site storage and storage duration. If the data is
stored on portable media and then the media is out of control,
the data are likely to take the risk of leakage. If the cloud
service providers do not provide off-site archiving, the
availability of the data will be threatened. Again, whether
storage duration is consistent with archival requirements?
Otherwise, this may result in the availability or privacy threats.
H. Destruction
When the data is no longer required, whether it has been
completely destroyed? Due to the physical characteristics of
storage medium, the data deleted may still exist and can be
restored. This may result in inadvertently disclose of sensitive
information.
IV. C
URRENT SECURITY SOLUTIONS FOR DATA SECURITY
AND PRIVACY PROTECTION
IBM developed a fully homomorphic encryption scheme in
June 2009. This scheme allows data to be processed without
being decrypted [12]. Roy I and Ramadan HE applied
decentralized information flow control (DIFC) and differential
privacy protection technology into data generation and
calculation stages in cloud and put forth a privacy protection
system called airavat [13]. This system can prevent privacy
leakage without authorization in Map-Reduce computing
process. A key problem for data encryption solutions is key
management. On the one hand, the users have not enough
expertise to manage their keys. On the other hand, the cloud
service providers need to maintain a large number of user keys.
The Organization for the Advancement of Structured
Information Standards (OASIS) Key Management
Interoperability Protocol (KMIP) is trying to solve such issues
[14].
About data integrity verification, because of data
communication, transfer fees and time cost, the users can not
first download data to verify its correctness and then upload the
data. And as the data is dynamic in cloud storage, traditional
data integrity solutions are no longer suitable. NEC Labs's
provable data integrity (PDI) solution can support public data
integrity verification [15]. Cong Wang proposed a
mathematical way to verify the integrity of the data
dynamically stored in the cloud [16].
In the data storage and use stages, Mowbray proposed a
client-based privacy management tool [17]. It provides a user-
centric trust model to help users to control the storage and use
of their sensitive information in the cloud. Munts-Mulero
discussed the problems that existing privacy protection
technologies (such as K anonymous, Graph Anonymization,
and data pre-processing methods) faced when applied to large
data and analyzed current solutions [18]. The challenge of data
privacy is sharing data while protecting personal privacy
information. Randike Gajanayake proposed a privacy
protection framework based on information accountability (IA)
components [19]. The IA agent can identify the users who are
accessing information and the types of information they use.
When inappropriate misuse is detected, the agent defines a set
of methods to hold the users accountable for misuse.
About data destruction, U.S. Department of Defense (DoD)
5220.22-M (the National Industrial Security Program
Operating Manual) shows two approved methods of data
(destruction) security, but it does not provide any specific
requirements for how these two methods are to be achieved
[20]. The National Institute of Standards and Technology
(NIST) Special Publication [21], 800-88, gives a“Guidelines
for Media Sanitization.”
V. C
ONCLUSION
Although cloud computing has many advantages, there are
still many actual problems that need to be solved. According to
a Gartner survey about cloud computing revenues, market size
for Public and Hybrid cloud is $59 billion and it will reach
USD 149B by 2014 with a compound annual growth rate of
20[22]. The revenue estimation implies that cloud computing is
a promising industry. But from another perspective, existing
vulnerabilities in the cloud model will increase the threats from
hackers.
According to service delivery models, deployment models
and essential features of the cloud computing, data security and
privacy protection issues are the primary problems that need to
be solved as soon as possible. Data security and privacy issues
650
exist in all levels in SPI service delivery models and in all
stages of data life cycle.
The challenges in privacy protection are sharing data while
protecting personal information. The typical systems that
require privacy protection are e-commerce systems that store
credit cards and health care systems with health data. The
ability to control what information to reveal and who can
access that information over the Internet has become a growing
concern. These concerns include whether personal information
can be stored or read by third parties without consent, or
whether third parties can track the web sites someone has
visited. Another concern is whether web sites which are visited
collect, store, and possibly share personal information about
users. The key to privacy protection in the cloud environment
is the strict separation of sensitive data from non-sensitive data
followed by the encryption of sensitive elements.
According to the analysis for data security and privacy
protection issues above, it is expected to have an integrated and
comprehensive security solution to meet the needs of defense
in depth. Regarding privacy protection, privacy data
identification and isolation are the primary tasks. They should
be considered during the design of cloud-based applications.
VI. F
UTURE WORK
For data security and privacy protection issues, the
fundamental challenges are separation of sensitive data and
access control. Our objective is to design a set of unified
identity management and privacy protection frameworks across
applications or cloud computing services. As mobility of
employees in organizations is relatively large, identity
management system should achieve more automatic and fast
user account provisioning and de-provisioning in order to
ensure no un-authorized access to organizations’ cloud
resources by some employees who has left the organizations.
Authorization and access control mechanisms should achieve a
unified, reusable and scalable access control model and meet
the need of fine-grained access authorization. Accountability
based privacy protection mechanisms will achieve dynamical
and real-time inform, authorization and auditing for the data
owners when their private data being accessed.
A
CKNOWLEDGMENT
We thank all sponsors in the footnote on the first page for
funding this ongoing research project and all volunteers for
their involving this research project. We would also like to
thank the anonymous referees for their constructive and
valuable comments.
R
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