Practical bootstrapping in quasilinear time

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Abstract

Gentry's "bootstrapping" technique (STOC 2009) constructs a fully homomorphic encryption (FHE) scheme from a "somewhat homomorphic" one that is powerful enough to evaluate its own decryption function. To date, it remains the only known way of obtaining unbounded FHE. Unfortunately, bootstrapping is computationally very expensive, despite the great deal of effort that has been spent on improving its efficiency. The current state of the art, due to Gentry, Halevi, and Smart (PKC 2012), is able to bootstrap "packed" ciphertexts (which encrypt up to a linear number of bits) in time only quasilinear Õ(λ) = λ·logO(1) λ in the security parameter. While this performance is asymptotically optimal up to logarithmic factors, the practical import is less clear: the procedure composes multiple layers of expensive and complex operations, to the point where it appears very difficult to implement, and its concrete runtime appears worse than those of prior methods (all of which have quadratic or larger asymptotic runtimes). In this work we give simple, practical, and entirely algebraic algorithms for bootstrapping in quasilinear time, for both "packed" and "non-packed" ciphertexts. Our methods are easy to implement (especially in the non-packed case), and we believe that they will be substantially more efficient in practice than all prior realizations of bootstrapping. One of our main techniques is a substantial enhancement of the "ring-switching" procedure of Gentry et al. (SCN 2012), which we extend to support switching between two rings where neither is a subring of the other. Using this procedure, we give a natural method for homomorphically evaluating a broad class of structured linear transformations, including one that lets us evaluate the decryption function efficiently. © 2013 International Association for Cryptologic Research.

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APA

Alperin-Sheriff, J., & Peikert, C. (2013). Practical bootstrapping in quasilinear time. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8042 LNCS, pp. 1–20). https://doi.org/10.1007/978-3-642-40041-4_1

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