Homomorphic SIM2D Operations: Single Instruction Much More Data

نویسندگان

  • Wouter Castryck
  • Ilia Iliashenko
  • Frederik Vercauteren
چکیده

In 2014, Smart and Vercauteren introduced a packing technique for homomorphic encryption schemes by decomposing the plaintext space using the Chinese Remainder Theorem. This technique allows to encrypt multiple data values simultaneously into one ciphertext and execute Single Instruction Multiple Data operations homomorphically. In this paper we improve and generalize their results by introducing a flexible Laurent polynomial encoding technique and by using a more fine-grained CRT decomposition of the plaintext space. The Laurent polynomial encoding provides a convenient common framework for all conventional ways in which input data types can be represented, e.g. finite field elements, integers, rationals, floats and complex numbers. Our methods greatly increase the packing capacity of the plaintext space, as well as one’s flexibility in optimizing the system parameters with respect to efficiency and/or security.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

FURISC: FHE Encrypted URISC Design

This paper proposes design of a Fully Homomorphic Ultimate RISC (FURISC) based processor. The FURISC architecture supports arbitrary operations on data encrypted with Fully Homomorphic Encryption (FHE) and allows the execution of encrypted programs stored in processors with encrypted memory addresses. The FURISC architecture is designed based on fully homomorphic single RISC instructions like S...

متن کامل

Private Compound Wildcard Queries using Fully Homomorphic Encryption

Fully homomorphic encryption (FHE) brings a paradigm shift in cryptographic engineering by enabling us to resolve various unsolved problems. Among them, this work solves the problem to design a private database query (PDQ) protocol that supports compound queries with wildcard conditions on encrypted databases using FHE. More precisely, we consider a setting where clients outsource an encrypted ...

متن کامل

GAZELLE: A Low Latency Framework for Secure Neural Network Inference

The growing popularity of cloud-based machine learning raises a natural question about the privacy guarantees that can be provided in such a setting. Our work tackles this problem in the context where a client wishes to classify private images using a convolutional neural network (CNN) trained by a server. Our goal is to build efficient protocols whereby the client can acquire the classificatio...

متن کامل

Comparing Tail Duplication with CompensationCode in Single Path Global

Global instruction scheduling allows operations to move across basic block boundaries to create tighter schedules. When operations move above control ow joins, some code duplication is generally necessary to preserve semantics. Tail duplication and compensation code are approaches to duplicating the necessary code, used by Superblock Scheduling and Trace Scheduling respectively. Compensation co...

متن کامل

QR factorization for the Cell Broadband Engine

The QR factorization is one of the most important operations in dense linear algebra, offering a numerically stable method for solving linear systems of equations including overdetermined and underdetermined systems. Modern implementations of the QR factorization, such as the one in the LAPACK library, suffer from performance limitations due to the use of matrix–vector type operations in the ph...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • IACR Cryptology ePrint Archive

دوره 2017  شماره 

صفحات  -

تاریخ انتشار 2017