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QPause: Quantum-Resistant Password-Protected Data Outsourcing for Cloud Storage

delete2024-05-01
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PRE
AI
J
Jingwei Jiang
D
Ding Wang *
G
Guoyin Zhang
DOI:10.1109/TSC.2023.3331000delete
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摘要

摘要

En 中文
Cloud storage provides an efficient and convenient way to manage data, but it also poses significant challenges to data security. The central issue with cloud storage is to ensure the ability of the data owner to control and manage the outsourced data. The password-protected secret sharing (PPSS) integrates password authentication and secret sharing to offer a fresh approach to secure private data. Users can share the risk of device corruption with a well-designed PPSS scheme and manage outsourced data with only human-memorizable passwords. To the best of our knowledge, none of the existing PPSS schemes can resist security threats in the post-quantum era, and there is an urgent need to design quantum-resistant solutions. However, post-quantum cryptography varies significantly from traditional cryptography, and it is challenging to design a quantum-resistant password-protected secret-sharing scheme for cloud storage. In this work, we take the first substantial step towards this challenge by proposing QPause, a quantum-resistant password-protected data outsourcing scheme for cloud storage. We first design a basic lattice-based PPSS secure against semi-honest adversaries with a secure channel. On this foundation, we propose a quantum-resistant round-optimal password-protected data outsourcing scheme against strong adversaries. In addition, we formally prove that our scheme is secure and robust under various attacks against adversaries with quantum computing capabilities. The comparison results show that our new scheme outperforms its foremost counterparts.
Keyword:
Cloud computing
Cryptography
Passwords
Servers
Encryption
Outsourcing
Authentication
Cloud storage
lattice
password protected
quantum security
secret sharing

期刊

IEEE Transactions on Services Computing 封面图
IEEE Transactions on Services Computing
IF:
5.8
论文数:
2.2K
被引数:
6.5K

机构

H
Harbin Engineering University
学者数:
1.9W
论文数: 1.3W
被引数: 1.3W
N
nankai university
学者数:
4.8W
论文数: 3.3W
被引数: 74
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