1. A ROBUST REPUTATION MANAGEMENT
MECHANISM IN THE FEDERATED CLOUD
Abstract:
In
the Infrastructure as a Service (IaaS) paradigm of cloud computing,
computational resources are available for rent. Although it offers a cost
efficient solution to virtual network requirements, low trust on the rented
computational resources prevents users from using it. To reduce the cost,
computational resources are shared, i.e., there exists multi-tenancy. As the
communication channels and other computational resources are shared, it creates
security and privacy issues. A user may not identify a trustworthy
co-tenant as the users are anonymous.
The user depends on the Cloud Provider (CP) to assign trustworthy co-tenants.
But, it is in the CP’s interest that it gets maximum utilization of its
resources. Hence, it allows maximum co-tenancy irrespective of the behaviours
of users. In this paper, we propose a robust reputation management mechanism
that encourages the CPs in a federated cloud to differentiate between good and
malicious users and assign resources in such a way that they do not share
resources. We show the correctness and the efficiency of the proposed
reputation management system using analytical and experimental analysis.
2.
ATTRIBUTE BASED STORAGE SUPPORTING
SECURE DEDUPLICATION OF ENCRYPTED DATA
IN CLOUD
Abstract: Attribute-based
encryption (ABE) has been widely used in cloud computing where a data provider
outsources his/her encrypted data to a cloud service provider, and can share
the data with users possessing specific credentials (or attributes). However,
the standard ABE system does not support secure deduplication, which is crucial
for eliminating duplicate copies of identical data inorder to save storage
space and network bandwidth. In this paper, we present an attribute-based
storage system with secure deduplication in a hybrid cloud setting, where a
private cloud is responsible for duplicate detection and a public cloud manages
the storage. Compared with the prior data deduplication systems, our system has
two advantages. Firstly, it can be used to confidentially share data with users
by specifying access policies rather than sharing decryption keys. Secondly, it
achieves the standard notion of semantic security for data confidentiality
while existing systems only achieve it by defining a weaker security notion. In
addition, we put forth a methodology to modify a ciphertext over one access
policy into ciphertexts of the same plaintext but under other access policies without
revealing the underlying plaintext.
3.
COST MINIMIZATION ALGORITHMS FOR
DATA CENTER MANAGEMENT
Abstract: Due
to the increasing usage of cloud computing applications, it is important to
minimize energy cost consumed by a data center, and simultaneously, to improve
quality of service via data center management. One promising approach is to
switch some servers in a data center to the idle mode for saving energy while
to keep a suitable number of servers in the active mode for providing timely
service. In this paper, we design both online and offline algorithms for this
problem. For the offline algorithm, we formulate data center management as a
cost minimization problem by considering energy cost, delay cost (to measure
service quality), and switching cost (to change servers’s active/idle mode).
Then, we analyze certain properties of an optimal solution which lead to a
dynamic programming based algorithm. Moreover, by revising the solution
procedure, we successfully eliminate the recursive procedure and achieve an
optimal offline algorithm with a polynomial complexity. For the online
algorithm, We design it by considering the worst case scenario for future workload.
In simulation, we show this online algorithm can always provide near-optimal
solutions.
4. CUSTOMER-SATISFACTION-AWARE OPTIMAL
MULTI SERVER CONFIGURATION FOR PROFIT MAXIMIZATION IN CLOUD COMPUTING
Abstract:
Along
with the development of cloud computing, an increasing number of enterprises
start to adopt cloud service, which promotes the emergence of many cloud
service providers. For cloud service providers, how to configure their cloud
service platforms to obtain the maximum profit becomes increasingly the focus
that they pay attention to. In this paper, we take customer satisfaction into
consideration to address this problem. Customer satisfaction affects the profit
of cloud service providers in two ways. On one hand, the cloud configuration
affects the quality of service which is an important factor affecting customer
satisfaction. On the other hand, the customer satisfaction affects the request
arrival rate of a cloud service provider. However, few existing works take
customer satisfaction into consideration in solving profit maximization
problem, or the existing works considering customer satisfaction do not give a
proper formalized definition for it. Hence, we firstly refer to the definition
of customer satisfaction in economics and develop a formula for measuring
customer satisfaction in cloud computing. And then, an analysis is given in
detail on how the customer satisfaction affects the profit. Lastly, taking into
consideration customer satisfaction, service-level agreement, renting price,
energy consumption and so forth, a profit maximization problem is formulated
and solved to get the optimal configuration such that the profit is maximized.
5.
IDENTITY-BASED REMOTE DATA
INTEGRITY CHECKING WITH PERFECT DATA PRIVACY PRESERVING FOR CLOUD STORAGE
Abstract:
Cloud storage
auditing is viewed as an important service to verify the integrity of the data
in public cloud. Current auditing protocols are all based on the assumption
that the client’s secret key for auditing is absolutely secure. However, such
assumption may not always be held, due to the possibly weak sense of security
and/or low security settings at the client.
If such a secret key for auditing is exposed, most of the current
auditing protocols would inevitably become unable to work. In this paper, we
focus on this new aspect of cloud storage auditing. We investigate how to
reduce the damage of the client’s key exposure in cloud storage auditing, and
give the first practical solution for this new problem setting.
6.
MINIMUM-COST CLOUD STORAGE SERVICE
ACROSS MULTIPLE CLOUD PROVIDERS
Abstract: Many Cloud Service Providers (CSPs)
provide data storage services with datacenters distributed worldwide. These datacenters provide different
Get/Put latencies and unit prices for resource utilization and reservation.
Thus, when selecting different CSPs’ datacenters, cloud customers of globally
distributed applications (e.g., online social networks) face two challenges
·
How to allocate data to worldwide
datacenters to satisfy application SLO (service level objective) requirements
including both data retrieval latency and availability, and
·
How to allocate data and reserve
resources in datacenters belonging to different CSPs to minimize the payment
cost. To handle these challenges, we first model the cost minimization problem under SLO constraints
using integer programming. Due to its NP-hardness,
we then introduce our heuristic solution, including a dominant-cost based data
allocation algorithm and an optimal resource reservation algorithm.
7.
SECURING CLOUD DATA UNDER KEY
EXPOSURE
Abstract:
Recent
news reveal a powerful attacker which breaks data confidentiality by acquiring
cryptographic keys, by means of coercion or backdoors in cryptographic
software. Once the encryption key is exposed, the only viable measure to
preserve data confidentiality is to limit the attacker’s access to the
ciphertext. This may be achieved, for example, by spreading ciphertext blocks
across servers in multiple administrative domains—thus assuming that the
adversary cannot compromise all of them. Nevertheless, if data is encrypted
with existing schemes, an adversary equipped with the encryption key, can still
compromise a single server and decrypt the ciphertext blocks stored therein. In
this paper, we study data confidentiality against an adversary which knows the
encryption key and has access to a large fraction of the ciphertext blocks. To
this end, we propose Bastion, a novel and efficient scheme that guarantees data
confidentiality even if the encryption key is leaked and the adversary has
access to almost all ciphertext blocks. We analyze the security of Bastion, and
we evaluate its performance by means of a prototype implementation. We also
discuss practical insights with respect to the integration of Bastion in
commercial dispersed storage systems. Our evaluation results suggest that
Bastion is well-suited for integration in existing systems since it incurs less
than 5% overhead compared to existing semantically secure encryption modes.
8.
A WORKFLOW MANAGEMENT SYSTEM FOR
SCALABLE DATA MINING ON CLOUDS
Abstract: The
pulling out of useful information from data is often a complex process that can
be expediently modeled as a data analysis workflow. When very large data sets
must be analyzed and/or complex data mining algorithms must be executed, data
analysis workflows may take very long times to complete their execution.
Therefore, efficient systems are required for the scalable execution of data
analysis workflows, by exploiting the computing services of the Cloud platforms
where data is increasingly being stored. The objective of the paper is to
demonstrate how Cloud software technologies can be integrated to implement an
effective environment for designing and executing scalable data analysis
workflows. We describe the design and implementation of the Data Mining Cloud
Framework (DMCF), a data analysis system that integrates a visual workflow
language and a parallel runtime with the Software-as-a-Service (SaaS) model.
DMCF was designed taking into account the needs of real data mining
applications, with the goal of simplifying the development of data mining
applications compared to generic workflow management systems that are not
specifically designed for this domain. The result is a high-level environment
that, through an integrated visual workflow language, minimizes the programming
effort, making easier to domain experts the use of common patterns specifically
designed for the development and the parallel execution of data mining
applications. The DMCF’s visual workflow language, system architecture and
runtime mechanisms are presented. We also discuss several data mining workflows
developed with DMCF and the scalability obtained executing such workflows on a
public Cloud.
9.
PRIVACY PROTECTION BASED ACCESS
CONTROL SCHEME IN CLOUD-BASED SERVICES
Abstract: With
the rapid development of the computer technology, cloud-based services have
become a hot topic. Cloud based services not only provide users with
convenience, but also bring many security issues. Therefore, the study of
access control scheme to protect users' privacy in cloud environment is of
great significance. In this paper, we present an access control system with
privilege separation based on privacy protection (PS-ACS). In the PS-ACS
scheme, we divide the users into personal domain (PSD) and public domain (PUD)
logically. In the PSD, we set read and write access permissions for users
respectively. The Key-Aggregate Encryption (KAE) is exploited to implement the
read access permission which improves the access efficiency. A high degree of
patient privacy is guaranteed simultaneously by exploiting an Improved
Attribute-based Signature (IABS) which can determine the users’ write access.
For the users of PUD, a hierarchical attribute-based encryption (HABE) is
applied to avoid the issues of single point of failure and complicated key
distribution. Function and performance testing result shows that the PS-ACS
scheme can achieve privacy protection in cloud based services. 10. PRACTICAL
PRIVACY-PRESERVING CONTENT-BASED RETRIEVAL IN CLOUD IMAGE REPOSITORIES
Abstract:
Storage requirements for visual data have been
increasing in recent years, following the emergence of many highly interactive
multimedia services and applications for mobile devices in both personal and
corporate scenarios. This has been a key driving factor for the adoption of
cloud-based data outsourcing solutions. However, outsourcing data storage to
the Cloud also leads to new security challenges that must be carefully
addressed, especially regarding privacy. In this paper we propose a secure
framework for outsourced privacy-preserving storage and retrieval in large
shared image repositories. Our proposal is based on IES-CBIR, a novel Image
Encryption Scheme that exhibits Content-Based Image Retrieval properties. The
framework enables both encrypted storage and searching using Content-Based
Image Retrieval queries while preserving privacy against honest-but-curious
cloud administrators. We have built a prototype of the proposed framework,
formally analyzed and proven its security properties, and experimentally
evaluated its performance and retrieval precision. Our results show that
IES-CBIR is provably secure, allows more efficient operations than existing
proposals, both in terms of time and space complexity, and paves the way for
new practical application scenarios.
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