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This research proposes a quantum algorithm to overcome the exponential complexity bottleneck of bootstrapping in fully homomorphic encryption (FHE), enabling polynomial-time evaluation of functions on encrypted data. By adapting classical blind rotation techniques to use quantum phase encoding, the study demonstrates how a single quantum server can drastically improve efficiency for privacy-preserving cloud computation. The work highlights significant time-space tradeoffs, suggesting that while high speed requires substantial qubit counts, reducing space complexity increases time requirements, offering new pathways for scalable quantum cryptographic tools.
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Quantum Blind Rotation for Fast Functional Bootstrapping

arXiv2 min read

arXiv:2409.20182v4 Announce Type: replace Abstract: Fully homomorphic encryption (FHE) enables privacy-preserving cloud computation, but its efficiency is often limited by the cost of bootstrapping. In particular, existing functional bootstrapping techniques have complexity exponential in the plaintext size. In this work, we show that employing a single quantum server can reduce this dependence. We propose a quantum functional bootstrapping algorithm that allows to evaluate any efficiently computable function in time polynomial in the plaintext size. For general functional bootstrapping over $l$-bit plaintexts, we obtain a time--space tradeoff: poly($l$)-time evaluation can be achieved with O$(2^l)$ qubits, while reducing the space complexity increases the time complexity. Technically, we extend a key classical cryptographic operation, known as \emph{blind rotation}, to the quantum setting by replacing polynomial-exponent encoding with quantum phase encoding. Underlying our extension are insights for the quantum extension of polynomial-based cryptographic tools that may gain dramatic speedups.

Abstract:Fully homomorphic encryption (FHE) enables privacy-preserving cloud computation, but its efficiency is often limited by the cost of bootstrapping. In particular, existing functional bootstrapping techniques have complexity exponential in the plaintext size. In this work, we show that employing a single quantum server can reduce this dependence. We propose a quantum functional bootstrapping algorithm that allows to evaluate any efficiently computable function in time polynomial in the plaintext size. For general functional bootstrapping over $l$-bit plaintexts, we obtain a time--space tradeoff: poly($l$)-time evaluation can be achieved with O$(2^l)$ qubits, while reducing the space complexity increases the time complexity. Technically, we extend a key classical cryptographic operation, known as \emph{blind rotation}, to the quantum setting by replacing polynomial-exponent encoding with quantum phase encoding. Underlying our extension are insights for the quantum extension of polynomial-based cryptographic tools that may gain dramatic speedups.

Quantum Physics (quant-ph); Computational Complexity (cs.CC); Cryptography and Security (cs.CR)

arXiv:2409.20182 [quant-ph]

(or arXiv:2409.20182v4 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2409.20182 Focus to learn more arXiv-issued DOI via DataCite

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Full text under the publisher's open licence · 239 words

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