Key-Aggregate Cryptosystem For Scalable Data Sharing In Cloud Storage

KEY-AGGREGATE CRYPTOSYSTEM FOR SCALABLE DATA SHARING IN CLOUD STORAGE

ABSTRACT:

Data sharing is an important functionality in cloud storage. In this article, we show how to securely, efficiently, and flexibly share data with others in cloud storage. We describe new public-key cryptosystems which produce constant-size ciphertexts such that efficient delegation of decryption rights for any set of ciphertexts are possible. The novelty is that one can aggregate any set of secret keys and make them as compact as a single key, but encompassing the power of all the keys being aggregated. In other words, the secret key holder can release a constant-size aggregate key for flexible choices of ciphertext set in cloud storage, but the other encrypted files outside the set remain confidential. This compact aggregate key can be conveniently sent to others or be stored in a smart card with very limited secure storage. We provide formal security analysis of our schemes in the standard model. We also describe other application of our schemes. In particular, our schemes give the first public-key patient-controlled encryption for flexible hierarchy, which was yet to be known.

EXISTING SYSTEM:

Considering data privacy, a traditional way to ensure it is to rely on the server to enforce the access control after authentication, which means any unexpected privilege escalation will expose all data. In a shared-tenancy cloud computing environment, things become even worse. Data from different clients can be hosted on separate virtual machines (VMs) but reside on a single physical machine. Data in a target VM could be stolen by instantiating another VM co-resident with the target one. Regarding availability of files, there are a series of cryptographic schemes which go as far as allowing a third-party auditor to check the availability of files on behalf of the data owner without leaking anything about the data, or without compromising the data owner’s anonymity. Likewise, cloud users probably will not hold the strong belief that the cloud server is doing a good job in terms of confidentiality. A cryptographic solution, with proven security relied on number-theoretic assumptions is more desirable, whenever the user is not perfectly happy with trusting the security of the VM or the honesty of the technical staff. These users are motivated to encrypt their data with their own keys before uploading them to the server.

DISADVANTAGES OF EXISTING SYSTEM:

·       Unexpected privilege escalation will expose all

·       It is not efficient.

·       Shared data will not be secure.

PROPOSED SYSTEM:

The best solution for the above problem is that Alice encrypts files with distinct public-keys, but only sends Bob a single (constant-size) decryption key. Since the decryption key should be sent via a secure channel and kept secret, small key size is always desirable. For example, we cannot expect large storage for decryption keys in the resource-constraint devices like smart phones, smart cards or wireless sensor nodes. Especially, these secret keys are usually stored in the tamper-proof memory, which is relatively expensive. The present research efforts mainly focus on minimizing the communication requirements (such as bandwidth, rounds of communication) like aggregate signature. However, not much has been done about the key itself.

ADVANTAGES OF PROPOSED SYSTEM:

·       It is more secure.

·       Decryption key should be sent via a secure channel and kept secret.

·       It is an efficient public-key encryption scheme which supports flexible delegation.

SYSTEM ARCHITECTURE:

 

SYSTEM CONFIGURATION:-

HARDWARE REQUIREMENTS:-

ü Processor                  -        Pentium –IV

ü Speed                        -        1.1 Ghz

ü RAM                         -        512 MB(min)

ü Hard Disk                 -        40 GB

ü Key Board                -        Standard Windows Keyboard

ü Mouse                       -        Two or Three Button Mouse

ü Monitor                     -        LCD/LED

SOFTWARE REQUIREMENTS:

•         Operating system :         Windows XP

•         Coding Language :         Java

•         Data Base             :         MySQL

•         Tool                     :         Net Beans IDE

REFERENCE:

Cheng-Kang Chu, Sherman S. M. Chow, Wen-Guey Tzeng, Jianying Zhou, and

Robert H. Deng, “Key-Aggregate Cryptosystem for Scalable Data Sharing in Cloud Storage” IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, Vol: 25,  Issue: 2,  Feb. 2014.

A Stochastic Model To Investigate Data Center Performance And Qos In Iaas Cloud Computing Systems

A STOCHASTIC MODEL TO INVESTIGATE DATA CENTER PERFORMANCE AND QOS IN IAAS CLOUD COMPUTING SYSTEMS

ABSTRACT:

Cloud data center management is a key problem due to the numerous and heterogeneous strategies that can be applied, ranging from the VM placement to the federation with other clouds. Performance evaluation of Cloud Computing infrastructures is required to predict and quantify the cost-benefit of a strategy portfolio and the corresponding Quality of Service (QoS) experienced by users. Such analyses are not feasible by simulation or on-the-field experimentation, due to the great number of parameters that have to be investigated. In this paper, we present an analytical model, based on Stochastic Reward Nets (SRNs), that is both scalable to model systems composed of thousands of resources and flexible to represent different policies and cloud-specific strategies. Several performance metrics are defined and evaluated to analyze the behavior of a Cloud data center: utilization, availability, waiting time, and responsiveness. A resiliency analysis is also provided to take into account load bursts. Finally, a general approach is presented that, starting from the concept of system capacity, can help system managers to opportunely set the data center parameters under different working conditions.

EXISTING SYSTEM:

In order to integrate business requirements and application level needs, in terms of Quality of Service (QoS), cloud service provisioning is regulated by Service Level Agreements (SLAs): contracts between clients and providers that express the price for a service, the QoS levels required during the service provisioning, and the penalties associated with the SLA violations. In such a context, performance evaluation plays a key role allowing system managers to evaluate the effects of different resource management strategies on the data center functioning and to predict the corresponding costs/benefits.

Cloud systems differ from traditional distributed systems. First of all, they are characterized by a very large number of resources that can span different administrative domains. Moreover, the high level of resource abstraction allows to implement particular resource management techniques such as VM multiplexing or VM live migration that, even if transparent to final users, have to be considered in the design of performance models in order to accurately understand the system behavior. Finally, different clouds, belonging to the same or to different organizations, can dynamically join each other to achieve a common goal, usually represented by the optimization of resources utilization. This mechanism, referred to as cloud federation, allows to provide and release resources on demand thus providing elastic capabilities to the whole infrastructure.

DISADVANTAGES OF EXISTING SYSTEM:

·       On-the-field experiments are mainly focused on the offered QoS, they are based on a black box approach that makes difficult to correlate obtained data to the internal resource management strategies implemented by the system provider.

·       Simulation does not allow to conduct comprehensive analyses of the system performance due to the great number of parameters that have to be investigated.

PROPOSED SYSTEM:

In this paper, we present a stochastic model, based on Stochastic Reward Nets (SRNs), that exhibits the above mentioned features allowing to capture the key concepts of an IaaS cloud system. The proposed model is scalable enough to represent systems composed of thousands of resources and it makes possible to represent both physical and virtual resources exploiting cloud specific concepts such as the infrastructure elasticity. With respect to the existing literature, the innovative aspect of the present work is that a generic and comprehensive view of a cloud system is presented. Low level details, such as VM multiplexing, are easily integrated with cloud based actions such as federation, allowing to investigate different mixed strategies. An exhaustive set of performance metrics are defined regarding both the system provider (e.g., utilization) and the final users (e.g., responsiveness).

ADVANTAGES OF PROPOSED SYSTEM:

To provide a fair comparison among different resource management strategies, also taking into account the system  elasticity, a performance evaluation approach is described. Such

an approach, based on the concept of system capacity, presents a holistic view of a cloud system and it allows system managers to study the better solution with respect to an established goal and to opportunely set the system parameters.

SYSTEM ARCHITECTURE:

SYSTEM CONFIGURATION:-

HARDWARE CONFIGURATION:-

     ü Processor               -       Pentium –IV

ü Speed                      -       1.1 Ghz

ü RAM                       -       256 MB(min)

ü Hard Disk                -       20 GB

ü Key Board               -       Standard Windows Keyboard

ü Mouse                      -       Two or Three Button Mouse

ü Monitor                    -       SVGA

SOFTWARE CONFIGURATION:-

ü Operating System                   : Windows XP

ü Programming Language         : JAVA

ü Java Version                   : JDK 1.6 & above.

REFERENCE:

Dario Bruneo, Member, IEEE-“ A Stochastic Model to Investigate Data Center Performance and QoS in IaaS Cloud Computing Systems”- IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2013.