Efficient and Scalable Query Authentication for Cloud-based Storage Systems with Multiple Data Sources (Aug-2017)
The aim of the project is to store the data files in cloud storage without making collision problem and then file will be retrieved using cryptograph method. Our project main aim is more security provided to file so we use double encryption also support multiple sources.
The main goal of this paper is to store the data in cloud storage and it can be retrieved by the clients with efficient and scalable compared to existing query authentication schemes offering support for multiple sources. Using our recently proposed multi-trapdoor hashing scheme, we develop a novel mechanism for authenticating query response in cloud-based storage systems, where data is populated by multiple data sources. The scheme allows clients to verify the integrity and authenticity of data returned by an outsourced database in response to their queries. The proposed scheme requires a small fixed sized authentication tag for each data element in the storage, and, unlike existing schemes in the literature, incurs (near-) constant computation and communication overheads for verifying the query response, regardless of the number of data elements returned by the query, or the number of sources. In particular as the size of the query response and the number of sources grows, all expensive cryptographic operations, like exponentiations, performed by the cloud and the client remain constant during query processing, with only trivial operations like multiplication, addition and hashing contributing to a highly manageable linear increase in computation cost. We evaluate the security of the proposed scheme and prove that forging the individual or aggregate authentication tags is infeasible under the discrete log assumption. We also demonstrate that the proposed scheme out-performs other existing schemes that provide similar features (in particular, support for multiple data sources) in terms of scalability, which is among the most important properties when considering cloud-based storage systems.