Access Restriction

Author Gorbunov, Sergey ♦ Vaikuntanathan, Vinod ♦ Wee, Hoeteck
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2015
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Cryptography ♦ Attribute-based encryption ♦ Fine-grained access control ♦ Lattices ♦ Learning with errors
Abstract In an attribute-based encryption (ABE) scheme, a ciphertext is associated with an ℓ-bit public index ind and a message $\textit{m},$ and a secret key is associated with a Boolean predicate $\textit{P}.$ The secret key allows decrypting the ciphertext and learning $\textit{m}$ if and only if $\textit{P}(ind)$ = 1. Moreover, the scheme should be secure against collusions of users, namely, given secret keys for polynomially many predicates, an adversary learns nothing about the message if none of the secret keys can individually decrypt the ciphertext. We present attribute-based encryption schemes for circuits of any arbitrary polynomial size, where the public parameters and the ciphertext grow linearly with the depth of the circuit. Our construction is secure under the standard learning with errors (LWE) assumption. Previous constructions of attribute-based encryption were for Boolean formulas, captured by the complexity class $NC^{1}.$ In the course of our construction, we present a new framework for constructing ABE schemes. As a by-product of our framework, we obtain ABE schemes for polynomial-size branching programs, corresponding to the complexity class $\textit{LOGSPACE},$ under quantitatively better assumptions.
ISSN 00045411
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-12-10
Publisher Place New York
e-ISSN 1557735X
Journal Journal of the ACM (JACM)
Volume Number 62
Issue Number 6
Page Count 33
Starting Page 1
Ending Page 33

Open content in new tab

   Open content in new tab
Source: ACM Digital Library