Publication Type

Journal Article

Version

publishedVersion

Publication Date

3-2018

Abstract

Attribute-based encryption (ABE) is an augmentation of public key encryption that allows users to encrypt and decrypt messages based on users' attributes. In a (t, s) threshold ABE, users who can decrypt a ciphertext must hold at least t attributes among the s attributes specified by the encryptor. At PKC 2010, Herranz, Laguillaumie and Raft& proposed the first threshold ABE with constant-size ciphertexts. In order to ensure the encryptor can flexibly select the attribute set and a threshold value, they use dummy attributes to satisfy the decryption requirement. The advantage of their scheme is that any addition or removal of the attributes will not require any change to users' private keys or public parameters. Unfortunately, the need for dummy attributes makes their scheme inefficient, since the computational cost of encryption is linear to the size of selected attribute set and dummy attribute set. In this work, we improve Herranz et al.'s work, and propose a new threshold ABE scheme which does not use any dummy attribute. Our scheme not only retains the nice feature of Herranz et al.'s scheme, but also offers two improvements in comparison to the previous work. Firstly, the computational costs of encryption and decryption are only linear in the size of the selected attribute set. Secondly, without any dummy attribute, most of the computations can be conducted without the knowledge of the threshold t. Hence, threshold change in the encryption phase does not require complete recomputation of the ciphertext. (C) 2017 Elsevier Inc. All rights reserved.

Keywords

Threshold attribute-based encryption, Constant size, Dummy attributes, Provable security

Discipline

Data Storage Systems | Information Security

Research Areas

Information Systems and Management

Publication

Information Sciences

Volume

429

First Page

349

Last Page

360

ISSN

0020-0255

Identifier

10.1016/j.ins.2017.11.037

Publisher

Elsevier

Additional URL

http://doi.org/10.1016/j.ins.2017.11.037

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