Toward Secure and Dependable Storage Services in Cloud Computing

Toward Secure and Dependable Storage Services in Cloud Computing

ABSTRACT:

Cloud storage enables users to remotely store their data and enjoy the on-demand high quality cloud applications without the burden of local hardware and software management. Though the benefits are clear, such a service is also relinquishing users’ physical possession of their outsourced data, which inevitably poses new security risks toward the correctness of the data in cloud. In order to address this new problem and further achieve a secure and dependable cloud storage service, we propose in this paper a flexible distributed storage integrity auditing mechanism, utilizing the homomorphic token and distributed erasure-coded data. The proposed design allows users to audit the cloud storage with very lightweight communication and computation cost. The auditing result not only ensures strong cloud storage correctness guarantee, but also simultaneously achieves fast data error localization, i.e., the identification of misbehaving server. Considering the cloud data are dynamic in nature, the proposed design further supports secure and efficient dynamic operations on outsourced data, including block modification, deletion, and append. Analysis shows the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks.

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 cannot 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.

DISADVANTAGES OF EXISTING SYSTEM:

These techniques, while can be useful to ensure the storage correctness without having users possessing data, cannot address all the security threats in cloud data storage, since they are all focusing on single server scenario and most of them do not consider dynamic data operations.

As an complementary approach, researchers have also proposed distributed protocols  for ensuring storage correctness across multiple servers or peers. Again, none of these distributed schemes is aware of dynamic data operations. As a result, their applicability in cloud data storage can be drastically limited.

PROPOSED SYSTEM:

In this paper, we propose an effective and flexible distributed scheme with explicit dynamic data support to ensure the correctness of users’ data in the cloud. We rely on erasure correcting code in the file distribution preparation to provide redundancies and guarantee the data dependability. This construction drastically reduces the communication and storage overhead as compared to the traditional replication-based file distribution techniques. By utilizing the homomorphic token with distributed verification of erasure-coded data, our scheme achieves the storage correctness insurance as well as data error localization: whenever data corruption has been detected during the storage correctness verification, our scheme can almost guarantee the simultaneous localization of data errors, i.e., the identification of the misbehaving server(s).

ADVANTAGES OF PROPOSED SYSTEM:

1. Compared to many of its predecessors, which only provide binary results about the storage state across the distributed servers, the challenge-response protocol in our work further provides the localization of data error.

2. Unlike most prior works for ensuring remote data integrity, the new scheme supports secure and efficient dynamic operations on data blocks, including: update, delete and append.

3. 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.

MODULES:

v System Model

v File Retrieval and Error Recovery

v Third Party Auditing

v Cloud Operations

MODULES DESCRIPTION:

1.     System Model

User: users, who have data to be stored in the cloud and rely on the cloud for data computation, consist of both individual consumers and organizations.

 Cloud Service Provider (CSP): a CSP, who has significant resources and expertise in building and managing distributed cloud storage servers, owns and operates live Cloud Computing systems.

 Third Party Auditor (TPA): an optional TPA, who has expertise and capabilities that users may not have, is trusted to assess and expose risk of cloud storage services on behalf of the users upon request.

2.     File Retrieval and Error Recovery

Since our layout of file matrix is systematic, the user can reconstruct the original file by downloading the data vectors from the first m servers, assuming that they return the correct response values. Notice that our verification scheme is based on random spot-checking, so the storage correctness assurance is a probabilistic one. We can guarantee the successful file retrieval with high probability. On the other hand, whenever the data corruption is detected, the comparison of pre-computed tokens and received response values can guarantee the identification of misbehaving server(s).

3.     Third Party Auditing

 As discussed in our architecture, in case the user does not have the time, feasibility or resources to perform the storage correctness verification, he can optionally delegate this task to an independent third party auditor, making the cloud storage publicly verifiable. However, as pointed out by the recent work, to securely introduce an effective TPA, the auditing process should bring in no new vulnerabilities towards user data privacy. Namely, TPA should not learn user’s data content through the delegated data auditing.

4.     Cloud Operations

(1) Update Operation

In cloud data storage, sometimes the user may need to modify some data block(s) stored in the cloud, we refer this operation as data update. In other words, for all the unused tokens, the user needs to exclude every occurrence of the old data block and replace it with the new one.

(2) Delete Operation

Sometimes, after being stored in the cloud, certain data blocks may need to be deleted. The delete operation we are considering is a general one, in which user replaces the data block with zero or some special reserved data symbol. From this point of view, the delete operation is actually a special case of the data update operation, where the original data blocks can be replaced with zeros or some predetermined special blocks.

(3) Append Operation

In some cases, the user may want to increase the size of his stored data by adding blocks at the end of the data file, which we refer as data append. We anticipate that the most frequent append operation in cloud data storage is bulk append, in which the user needs to upload a large number of blocks (not a single block) at one time.

 

SYSTEM CONFIGURATION:-

HARDWARE REQUIREMENTS:-

ü Processor             -Pentium –III

ü Speed                             -    1.1 Ghz

ü RAM                    -    256 MB(min)

ü Hard Disk            -   20 GB

ü Floppy Drive       -    1.44 MB

ü Key Board            -    Standard Windows Keyboard

ü Mouse                  -    Two or Three Button Mouse

ü Monitor                -    SVGA

SOFTWARE REQUIREMENTS:-

v   Operating System          : Windows95/98/2000/XP

v   Application  Server       : Tomcat5.0/6.X                                        

v   Front End                      : Java, JSP

v    Script                            : JavaScript.

v   Server side Script          : Java Server Pages.

v   Database                        : MYSQL

REFERENCE:

Cong Wang, Qian Wang, Kui Ren, Ning Cao, and Wenjing Lou,” Toward Secure and Dependable Storage Services in Cloud Computing”, IEEE TRANSACTIONS ON SERVICES COMPUTING, VOL. 5, NO. 2, APRIL-JUNE 2012.