Publicly Verifiable Inner Product Evaluation Over Outsourced Data Streams Under Multiple Keys
It is appealing to many companies and individuals to upload data streams to a resource-rich cloud server for internal product evaluation, an essential building block in many popular stream applications (e.g. statistical monitoring). On the other hand, verifying the remote computation result plays a crucial role in addressing the trust issue. Publicly Verifiable Inner Product Evaluation over Outsourced Data Streams under Multiple Keys Since the outsourced data collection is likely to come from multiple data sources, it is desired that the system can identify the originator of errors by assigning a unique secret key to each data source, which requires the internal product verification to be performed under the different keys of any two parties.
H/W System Configuration
Speed : 1.1 GHz
RAM : 256 MB(min)
Hard Disk : 20 GB
Floppy Drive : 1.44 MB
Key Board : Standard Windows Keyboard
Mouse : Two or Three Button Mouse
Monitor : SVGA
S/W System Configuration
Platform : cloud computing
Operating system : Windows Xp,7,
Server : WAMP/Apache
Working on : Browser Like Firefox, IE
In this paper, we introduce a novel homomorphic verifiable tag technique and design under multiple keys an efficient and publicly verifiable internal product computation scheme on dynamic outsourced data streams. In order to support matrix product, we also extend the internal product scheme. Compared to the existing works under the single-key setting, our scheme aims at the more challenging multi-key scenario, i.e. allowing multiple data sources with different secret keys to upload their endless data streams and delegate the corresponding computations to a third-party server, while traceability can still be provided on demand.