International Association
for Cryptologic Research

Fully Homomorphic Encryption (FHE) is a powerful Privacy-Enhancing Technology (PET) that enables computations on encrypted data without having access to the secret key. While FHE holds immense potential for enhancing data privacy and security, creating its practical applications is associated with many difficulties. A significant barrier is the absence of easy-to-use, standardized components that developers can utilize as foundational building blocks. Addressing this gap requires constructing a comprehensive library of FHE components, a complex endeavor due to multiple inherent problems. We propose a competition-based approach for building such a library. More concretely, we present FHERMA, a new challenge platform that introduces black-box and white-box challenges, and fully automated evaluation of submitted FHE solutions. The initial challenges on the FHERMA platform are motivated by practical problems in machine learning and blockchain. The winning solutions get integrated into an open-source library of FHE components, which is available to all members of the PETs community under the Apache 2.0 license.