利用加密反向防火墙进行无证书代理再加密,实现安全的云数据共享

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
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引用次数: 0

摘要

云计算使数据共享比以往任何时候都更加方便。然而,数据安全是阻碍云计算广泛应用的一个主要问题。云计算中数据安全共享的一个潜在解决方案是代理再加密(PRE),它允许代理将加密数据从一个密钥转换为另一个密钥,而无需访问明文。使用 PRE 时,会出现各种挑战,包括可信第三方泄漏信息、串通攻击以及与撤销相关的问题。为了克服这些挑战,本文提出了一种新型的无证书代理重加密与加密反向防火墙安全云数据共享(CLPRE-CRF)。这一新方案能够通过公共云将加密数据从数据所有者安全地分发到用户。同时,CLPRE-CRF 方案可在方案遭到破坏时抵御秘密信息外泄和密文伪造。此外,该方案还提供了灵活的撤销机制,以防止未经授权访问私人数据。安全性分析表明,CLPRE-CRF 可抵御选择性纯文本攻击和串通攻击。此外,性能评估表明,我们的方案在加密和解密算法中分别减少了 14% 和 22% 的计算成本。因此,所提出的 CLPRE-CRF 方案非常适合云计算环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Certificateless Proxy Re-encryption with Cryptographic Reverse Firewalls for Secure Cloud Data Sharing

Cloud computing has enabled data-sharing to be more convenient than ever before. However, data security is a major concern that prevents cloud computing from being widely adopted. A potential solution to secure data-sharing in cloud computing is proxy re-encryption (PRE), which allows a proxy to transform encrypted data from one key to another without accessing the plaintext. When using PRE, various challenges arise, including the leak of information by a trusted third party, collusion attacks, and issues associated with revocation. To overcome these challenges, this paper proposes a novel Certificateless Proxy Reencryption with Cryptographic Reverse Firewall for Secure Cloud Data Sharing (CLPRE-CRF). The new scheme enables secure distribution of encrypted data from a data owner to users through public clouds. Meanwhile, the CLPRE-CRF scheme can resist exfiltration of secret information and forgery of ciphertext in case the scheme is compromised. In addition, the scheme provides a flexible revocation mechanism to prevent unauthorized access to private data. The security analysis demonstrates that the CLPRE-CRF resists chosen-plaintext attacks and collusion attacks. Moreover, performance evaluation indicates that our scheme achieves a 14% and 22% reduction in computation costs during the encryption and decryption algorithms, respectively. Therefore, the proposed CLPRE-CRF scheme is well-suited for cloud computing environments.

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来源期刊
CiteScore
19.90
自引率
2.70%
发文量
376
审稿时长
10.6 months
期刊介绍: Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.
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