Biblio

In the existing remote data integrity checking schemes, dynamic update operates on block level, which usually restricts the location of the data inserted in a file due to the fixed size of a data block. In this paper, we propose a remote data integrity checking scheme with fine-grained update for big data storage. The proposed scheme achieves basic operations of insertion, modification, deletion on line level at any location in a file by designing a mapping relationship between line level update and block level update. Scheme analysis shows that the proposed scheme supports public verification and privacy preservation. Meanwhile, it performs data integrity checking with low computation and communication cost.

There are many risks in moving data into public storage environments, along with an increasing threat around large-scale data leakage. Secret sharing scheme has been proposed as a keyless and resilient mechanism to mitigate this, but scaling through large scale data infrastructure has remained the bane of using secret sharing scheme in big data storage and retrievals. This work applies secret sharing methods as used in cryptography to create robust and secure data storage and retrievals in conjunction with data fragmentation. It outlines two different methods of distributing data equally to storage locations as well as recovering them in such a manner that ensures consistent data availability irrespective of file size and type. Our experiments consist of two different methods - data and key shares. Using our experimental results, we were able to validate previous works on the effects of threshold on file recovery. Results obtained also revealed the varying effects of share writing to and retrieval from storage locations other than computer memory. The implication is that increase in fragment size at varying file and threshold sizes rather than add overheads to file recovery, do so on creation instead, underscoring the importance of choosing a varying fragment size as file size increases.