Search Results for author:
Found 2 papers, 0 papers with code
When Evolutionary Computation Meets Privacy
To this end, in this paper, we discuss three typical optimization paradigms (i. e., \textit{centralized optimization, distributed optimization, and data-driven optimization}) to characterize optimization modes of evolutionary computation and propose BOOM to sort out privacy concerns in evolutionary computation.
A Survey of Secure Computation Using Trusted Execution Environments
To the best of our knowledge, this article is the first survey to review TEE-based secure computation protocols and the comprehensive comparison can serve as a guideline for selecting suitable protocols for deployment in practice.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
