Cloud Auditing

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This section explains the various systems which were pro-posed by other researchers with pros and cons. The Y. Zhu, H. Wang, Z. Hu, et al. [11], proposed a scheme which checks the integrity of data by traditional cryptography method. In this, the data is stored at the cloud and second copy is maintained at user side to check the integrity of data. But this results in waste of space and increased expense of transmission between user and data storage. Thus, it is effective but incredibly costly to retain data at both sides. Alina Oprea, Michael K. Reiter, Ke Yang [12] provided a solution to find integrity of data by using block identity number and random block number which are insufficient to check the integrity of data. Sanket Sandesh Shahane and Raj B. Kulkarni [13] explained the cloud characteristics, services provided by cloud, properties of data integrity, necessity with benefits of cloud and necessity with applications of Auditing. The paper explained about the three processes like Tag generation, Sampling auditing and Dynamic Auditing which supports third party auditing. H.C Hsiao, Y.H Lin, et al. [14] projected a study of user-friendly hash that describes some schemes which are quickest and most accurate. In this study, Chinese, Korean and Japanese characters are com-pared with each other for using them as hash values. It had described the strength and weakness of each scheme. Wang Qian, Cong Wang, Kui Ren, Wenjing Lou and Jin Li [15] explained that Data Storage System would attempt to hide the errors like data lost during relocation, power failure, etc. from the clients for the betterment and maintaining reputation of their own. The service provider might neglect to keep or deliberately delete hardly ever or never accessed ... ... middle of paper ... ...t generation approach data storage than old ones and new ways to secure like chalk and cheese way. It proposed the architecture and functioning of a database system with reliability, however, adds little load on trusted storage for storing the hash and log values. The untrusted programs were unable to read the database or modify it undetectably due to encrypted database and validated against a collision-resistant hash kept in honest storage. The model protects data and metadata evenly through Trusted Data Base (TDB) that combines encryption and hashing together. The data placed at storage server with the help of the checkpoints which made for data backup, if attacker attacks the system the data could be rolled back up to checkpoint, however, if checkpoints got lost or erased due to some internal or external reason then backup becomes a problem rather than solution.

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