
A Privacy-Preserving Outsourced Functional Computation Framework Across Large-Scale Multiple Encrypted Domains
Abstract
In this paper, we propose a framework for privacy-preserving outsourced functional computation across multiple encrypted domains on a large scale, which we refer to as POFD. A Privacy-Preserving Outsourced Functional Computation Framework Across Large-Scale Multiple Encrypted Domains With POFD, a user can obtain the output of a function computed over encrypted data from multiple domains while protecting the privacy of the function itself, its input and output. Specifically, to trade the levels of privacy protection and performance, we introduce two notions of POFD, the basic POFD and its enhanced version.
System Configuration
Platform : cloud computing
Conclusion
In this paper, we proposed a new framework called POFD for privacy-preserving outsourced functional computation across multiple encrypted domains on a large scale. By running the POFD, a user can get the final results efficiently in one round communication without compromising the user’s query privacy and data privacy. A new public key cryptosystem was designed to support distributed decryption as a key component of POFD.