Cloud computing design
#1

Cloud computing is a style of computing that provides virtualized resources as a service over the internet. The clientâ„¢s data is given to a third party (the cloud service provider) for storage. They lose control of their information and they are unaware of the location where their data is stored. This means that their data is vulnerable to external attacks. Firstly, in the physical infrastructure (the datacenter behind the cloud) different customers workloads are placed in the same physical machine. Secondly, concerns about malicious software take an important place. Failure of one physical machine should not deter the working of others. In this project, we implement a model to solve these issues. This model is based on the basic idea of removing abstraction from the cloud infrastructure. Thereby, allowing the user to evaluate the security properties and measures of the platform before they provision their data in the cloud. Further, isolation policies are deployed to provide workload isolation and data security.
Cloud computing can be divided into three areas:

¢ SaaS (software-as-a-service). WAN-enabled application services (e.g., Google Apps, Salesforce.com, WebEx)

¢ PaaS (platform-as-a-service). Foundational elements to develop new applications (e.g., Coghead, Google Application Engine)

¢ IaaS (infrastructure-as-a-service). Providing computational and storage infrastructure in a centralized, location-transparent service (e.g., Amazon)


Cloud computing characteristics

¢ Massive, abstracted infrastructure

¢ Dynamic allocation, scaling, movement of applications

¢ Pay per use

¢ No long-term commitments

¢ On-demand self-service

¢ Ubiquitous network access

¢ No hardware or software to install
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#2
[attachment=6528]
Ensuring Data Storage Security in Cloud Computing



ABSTRACT
Cloud computing has been envisioned as the next-generation architecture of IT enterprise. In contrast to traditional solutions, where the IT services are under proper physical, logical and personnel controls, cloud computing moves the application software and databases to the large data centers, where the management of the data and services may not be fully trustworthy. This unique attribute, however, poses many new security challenges which have not been well understood. In this article, we focus on cloud data storage security, which has always been an important aspect of quality of service. To ensure the correctness of users' data in the cloud, we propose an effective and flexible distributed scheme with two salient features, opposing to its predecessors. By utilizing the homomorphic token with distributed verification of erasure-coded data, our scheme achieves the integration of storage correctness insurance and data error localization, i.e., the identification of misbehaving server (s). Unlike most prior works, the new scheme further supports secure and efficient dynamic operations on data blocks, including: data update, delete and append. Extensive security and performance analysis shows that the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks.




System Architecture:


Existing System:
From the perspective of data security, which has always been an important aspect of quality of service, Cloud Computing inevitably poses new challenging security threats for number of reasons.

1 . Firstly, traditional cryptographic primitives for the purpose of data security protection can not be directly adopted due to the users’ loss control of data under Cloud Computing. Therefore, verification of correct data storage in the cloud must be conducted without explicit knowledge of the whole data. Considering various kinds of data for each user stored in the cloud and the demand of long term continuous assurance of their data safety, the problem of verifying correctness of data storage in the cloud becomes even more challenging.

2 . Secondly, Cloud Computing is not just a third party data warehouse. The data stored in the cloud may be frequently updated by the users, including insertion, deletion, modification, appending, reordering, etc. To ensure storage correctness under dynamic data update is hence of paramount importance.
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#3

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