Publicly Auditable Inner Product Evaluation from Different Data Sources under Ontime Generated Multiple Keys

Nowadays verifying the result of the remote computation plays a crucial role in addressing in issue of trust. The outsourced data collection comes for multiple data sources to diagnose the originator of errors by allotting each data sources a unique secrete key which requires the inner product conformation to be performed under any two parties different keys. The existing work under single key setting, but our scheme focuses on multi-key scenario. This allows multiple data sources with different secrete keys to upload their data streams and delegate the computation to the third party server. A novel homomorphic encryption technique to publicly verify the out sourced inner product computation on the dynamic data streams and extend to support the verification of the matrix product computation. The multi-key setting is given different secrete keys, multiple data sources can be upload their data streams along with their respective verifiable homomorphic tag. The client should allow choosing any portion in the data streams for queries. The communication between the client and server is independent of input size. The inner product evaluation can be performed by any two sources and the result can be verified by using the particular tag.