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TFHE: Fast Fully Homomorphic Encryption over the Torus.
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TLDR
A new circuit bootstrapping is presented that makes the leveled mode of TFHE composable and which is fast enough to speed up arithmetic functions, compared to the gate bootstrapped approach.Abstract:
This work describes a fast fully homomorphic encryption scheme over the torus (TFHE) that revisits, generalizes and improves the fully homomorphic encryption (FHE) based on GSW and its ring variants. The simplest FHE schemes consist in bootstrapped binary gates. In this gate bootstrapping mode, we show that the scheme FHEW of Ducas and Micciancio (Eurocrypt, 2015) can be expressed only in terms of external product between a GSW and an LWE ciphertext. As a consequence of this result and of other optimizations, we decrease the running time of their bootstrapping from 690 to 13 ms single core, using 16 MB bootstrapping key instead of 1 GB, and preserving the security parameter. In leveled homomorphic mode, we propose two methods to manipulate packed data, in order to decrease the ciphertext expansion and to optimize the evaluation of lookup tables and arbitrary functions in $${\mathrm {RingGSW}}$$-based homomorphic schemes. We also extend the automata logic, introduced in Gama et al. (Eurocrypt, 2016), to the efficient leveled evaluation of weighted automata, and present a new homomorphic counter called $$\mathrm {TBSR}$$, that supports all the elementary operations that occur in a multiplication. These improvements speed up the evaluation of most arithmetic functions in a packed leveled mode, with a noise overhead that remains additive. We finally present a new circuit bootstrapping that converts $$\mathsf {LWE}$$ ciphertexts into low-noise $${\mathrm {RingGSW}}$$ ciphertexts in just 137 ms, which makes the leveled mode of TFHE composable and which is fast enough to speed up arithmetic functions, compared to the gate bootstrapping approach. Finally, we provide an alternative practical analysis of LWE based schemes, which directly relates the security parameter to the error rate of LWE and the entropy of the LWE secret key, and we propose concrete parameter sets and timing comparison for all our constructions.read more
Citations
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Book ChapterDOI
Fast Homomorphic Evaluation of Deep Discretized Neural Networks
TL;DR: The rise of machine learning as a service multiplies scenarios where one faces a privacy dilemma: either sensitive user data must be revealed to the entity that evaluates the cognitive model, or the model itself must be reveal to the user so that the evaluation can take place locally.
Journal ArticleDOI
Data Security and Privacy Protection for Cloud Storage: A Survey
Pan Yang,Naixue Xiong,Jingli Ren +2 more
TL;DR: This paper makes a comprehensive review of the literatures on data security and privacy issues, data encryption technology, and applicable countermeasures in cloud storage system, and gives an overview of cloud storage, including definition, classification, architecture and applications.
Proceedings ArticleDOI
CHET: an optimizing compiler for fully-homomorphic neural-network inferencing
Roshan Dathathri,Olli Saarikivi,Hao Chen,Kim Laine,Kristin E. Lauter,Saeed Maleki,Madanlal Musuvathi,Todd Mytkowicz +7 more
TL;DR: CHET is a domain-specific optimizing compiler designed to make the task of programming FHE applications easier, and generates homomorphic circuits that outperform expert-tuned circuits and makes it easy to switch across different encryption schemes.
Journal ArticleDOI
Homomorphic Encryption for Machine Learning in Medicine and Bioinformatics
TL;DR: The state of fully homomorphic encryption for privacy-preserving techniques in machine learning and bioinformatics is reviewed, along with descriptions of how these methods can be implemented in the encrypted domain.
Journal ArticleDOI
CHIMERA: Combining Ring-LWE-based Fully Homomorphic Encryption Schemes
TL;DR: A practical hybrid solution for combining and switching between three popular Ring-LWE-based FHE schemes: TFHE, B/FV and HEAAN is proposed by first mapping the different plaintext spaces to a common algebraic structure and then by applying efficient switching algorithms.
References
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Proceedings ArticleDOI
Fully homomorphic encryption using ideal lattices
TL;DR: This work proposes a fully homomorphic encryption scheme that allows one to evaluate circuits over encrypted data without being able to decrypt, and describes a public key encryption scheme using ideal lattices that is almost bootstrappable.
Journal ArticleDOI
The Design and Implementation of FFTW3
Matteo Frigo,Steven G. Johnson +1 more
TL;DR: It is shown that such an approach can yield an implementation of the discrete Fourier transform that is competitive with hand-optimized libraries, and the software structure that makes the current FFTW3 version flexible and adaptive is described.
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On lattices, learning with errors, random linear codes, and cryptography
TL;DR: A public-key cryptosystem whose hardness is based on the worst-case quantum hardness of SVP and SIVP, and an efficient solution to the learning problem implies a quantum, which can be made classical.
Proceedings ArticleDOI
Leveled) fully homomorphic encryption without bootstrapping
TL;DR: A novel approach to fully homomorphic encryption (FHE) that dramatically improves performance and bases security on weaker assumptions, using some new techniques recently introduced by Brakerski and Vaikuntanathan (FOCS 2011).
Posted Content
Fully Homomorphic Encryption over the Integers.
TL;DR: In this paper, a somewhat homomorphic encryption scheme using elementary modular arithmetic is described. But the main appeal of their approach is the conceptual simplicity. And the security of their scheme is reduced to finding an approximate integer gcd, i.e., given a list of integers that are near-multiples of a hidden integer, output that hidden integer.