Paper 2022/149

Putting up the swiss army knife of homomorphic calculations by means of TFHE functional bootstrapping

Pierre-Emmanuel Clet, CEA
Martin Zuber, CEA
Aymen Boudguiga, CEA
Renaud Sirdey, CEA
Cédric Gouy-Pailler, CEA

In this work, we first propose a new functional bootstrapping with TFHE for evaluating any function of domain and codomain the real torus T by using a small number of bootstrappings. This result improves some aspects of previous approaches: like them, we allow for evaluating any functions, but with better precision. In addition, we develop more efficient multiplication and addition over ciphertexts building on the digit-decomposition approach. As a practical application, our results lead to an efficient implementation of ReLU, one of the most used activation functions in deep learning. The paper is concluded by extensive experimental results comparing each building block as well as their practical relevance and trade-offs.

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FHE TFHE functional bootstrapping
Contact author(s)
pierre-emmanuel clet @ cea fr
martin zuber @ cea fr
aymen boudguiga @ cea fr
renaud sirdey @ cea fr
cedric gouy-pailler @ cea fr
2022-09-15: last of 2 revisions
2022-02-12: received
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      author = {Pierre-Emmanuel Clet and Martin Zuber and Aymen Boudguiga and Renaud Sirdey and Cédric Gouy-Pailler},
      title = {Putting up the swiss army knife of homomorphic calculations by means of {TFHE} functional bootstrapping},
      howpublished = {Cryptology ePrint Archive, Paper 2022/149},
      year = {2022},
      note = {\url{}},
      url = {}
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