Practical applications of improved Gaussian sampling for trapdoor lattices

Gür, Kamil D. and Polyakov, Yuriy and Rohloff, Kurt and Ryan, Gerard W. and Sajjadpour, Hadi and Savaş, Erkay (2019) Practical applications of improved Gaussian sampling for trapdoor lattices. IEEE Transactions on Computers, 68 (4). pp. 570-584. ISSN 0018-9340 (Print) 1557-9956 (Online)

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Abstract

Lattice trapdoors are an important primitive used in a wide range of cryptographic protocols, such as identity-based encryption (IBE), attribute-based encryption, functional encryption, and program obfuscation. In this paper, we present software implementations of the Gentry-Peikert-Vaikuntanathan (GPV) digital signature, IBE and ciphertext-policy attribute-based encryption (CP-ABE) schemes based on an efficient Gaussian sampling algorithm for trapdoor lattices, and demonstrate that these three important cryptographic protocols are practical. One important aspect of our implementation is that it supports prime moduli, which are required in many cryptographic schemes. Also, our implementation uses bases larger than two for the gadget matrix whereas most previous implementations use the binary base. We show that the use of higher bases significantly decreases execution times and storage requirements. We adapt IBE and CP-ABE schemes originally based on learning with errors (LWE) hardness assumptions to a more efficient Ring LWE (RLWE) construction. To the best of our knowledge, ours are the first implementations employing the Gaussian sampling for non-binary bases of the gadget matrix. The experimental results demonstrate that our lattice-based signature, IBE and CP-ABE implementations, which are based on standard assumptions with post-quantum security, provide a performance comparable to the recent state-of-the-art implementation works based on stronger/non-post-quantum assumptions.
Item Type: Article
Uncontrolled Keywords: Lattice-based cryptography; RLWE; identity-based encryption; attribute-based encryption; GPV digital signature; Gaussian sampler
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng.
Faculty of Engineering and Natural Sciences
Depositing User: Erkay Savaş
Date Deposited: 21 May 2019 10:42
Last Modified: 26 Apr 2022 10:03
URI: https://research.sabanciuniv.edu/id/eprint/37024

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