IDENTIFY-BASED DYNAMIC DATA AUDITING FOR BIG DATA STORAGE

ABSTARCT :

Identity-based remote data auditing schemes can verify data integrity and provide a simple identity authentication and management for multiple users. However, prior works on identity-based remote data auditing lack the support of dynamic operations. In these schemes, tag generation is linked to the index of data block, which is related to update operations such as modification, insertion and deletion. If users perform dynamic operations on a data block, the tags of all subsequent blocks need to be modified. It means that if users want to update data on a big data platform, they have to download the whole file, update the file and send the updated file to the big data platform. Such pattern will bring huge communication overhead. In this paper, we propose an identity-based dynamic data auditing scheme which supports dynamic data operations, including modification, insertion and deletion. As far as we know, there is still no other identity-based data auditing scheme that supports dynamic operations. In particular, to achieve efficient dynamic operations, we use the data structure of Merkle hash tree for block tag authentication, which helps update data with integrity assurance. Analyses of security and performance show that the proposed scheme is efficient and secure.

EXISTING SYSTEM :

? In Existing system, users can store their data in the cloud to avoid the expenditure of local data storage and maintenance. ? To ensure the integrity of the data stored in the cloud, many data integrity auditing schemes have been proposed. ? In most, if not all, of the existing schemes, a user needs to employ his private key to generate the data authenticators for realizing the data integrity auditing.

DISADVANTAGE :

? This scheme has a security issue that the server can use a valid response to answer all challenges. ? Identity-based cryptography has been exploited by researchers in the public auditing protocols to avoid the potential key management problem. ? It is a problem worthy of study that how to minimize the DO’s computational cost while ensuring the functions and security features.

PROPOSED SYSTEM :

• To deal with the data integrity issue, the concept of data integrity auditing has been proposed, which usually adopts a third party auditor to audit whether the service provider has stored the users’ data intact. • Many public data integrity auditing protocols have been proposed by researchers to achieve different security and functional features, such as privacy preserving, storage correctness, batch verification, and dynamic support. • Although there are many schemes have been proposed in the field of public auditing for cloud computing, there is room for further research in this field.

ADVANTAGE :

? With this data structure, our scheme efficiently supports dynamic data operations, including modification, insertion and deletion. ? Although SPDP scheme is based on symmetric key and has high efficiency, it does not support public verification. ? Cloud storage, as it can provide users with efficient, secure and low-cost storage services without having to build a storage platform by themselves, has become a popular application along with the wide spread of cloud computing.