Paper 2022/180

Towards Globally Optimized Hybrid Homomorphic Encryption - Featuring the Elisabeth Stream Cipher

Orel Cosseron, Clément Hoffmann, Pierrick Méaux, and François-Xavier Standaert


Hybrid Homomorphic Encryption (HHE) reduces the amount of computation client-side and band- width usage in a Fully Homomorphic Encryption (FHE) framework. HHE requires the usage of specific sym- metric schemes that can be evaluated homomorphically efficiently. In this paper, we introduce the paradigm of Group Filter Permutator (GFP) as a generalization of the Improved Filter Permutator paradigm introduced by M ́eaux et al. From this paradigm, we specify Elisabeth , a family of stream cipher and give an instance: Elisabeth-4 . After proving the security of this scheme, we provide a Rust implementation of it and ensure its performance is comparable to state-of-the-art HHE. The true strength of Elisabeth lies in the available opera- tions server-side: while the best HHE applications were limited to a few multiplications server-side, we used data sent through Elisabeth-4 to homomorphically evaluate a neural network inference. Finally, we discuss the improvement and loss between the HHE and the FHE framework and give ideas to build more efficient schemes from the Elisabeth family

Available format(s)
Secret-key cryptography
Publication info
Preprint. MINOR revision.
homomorphic encryptionhybrid homomorphic encryptionElisabethstream-ciphersGroup Filter PermutatorTFHE
Contact author(s)
orel cosseron @ zama ai
clement hoffmann @ uclouvain be
pierrick meaux @ uclouvain be
fstandae @ uclouvain be
2022-02-22: last of 2 revisions
2022-02-20: received
See all versions
Short URL
Creative Commons Attribution


      author = {Orel Cosseron and Clément Hoffmann and Pierrick Méaux and François-Xavier Standaert},
      title = {Towards Globally Optimized Hybrid Homomorphic Encryption - Featuring the Elisabeth Stream Cipher},
      howpublished = {Cryptology ePrint Archive, Paper 2022/180},
      year = {2022},
      note = {\url{}},
      url = {}
Note: In order to protect the privacy of readers, does not use cookies or embedded third party content.