使用响应式zkSNARK为移动计算提供可靠的区块链外包解密CP-ABE

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Dongliang Cai , Borui Chen , Liang Zhang , Kexin Li , Haibin Kan
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引用次数: 0

摘要

基于密文策略属性的加密(cipher - policy - Attribute-Based Encryption, CP-ABE)是一种很有前途的移动计算访问控制解决方案。然而,繁重的解密开销阻碍了它的广泛采用。解决此问题的一般方法是将解密外包给解密云服务器(DCS)。现有方案实现了可验证性,但缺乏有效的豁免机制来保护诚实的DCS免受虚假索赔。在本文中,我们提出了一个支持区块链的可靠外包解密CP-ABE框架,该框架在不向密文添加冗余信息的情况下实现了可验证性和可豁免性。我们使用zkSNARK有效地验证区块链上的外包结果,并引入挑战响应机制来解决证明生成的高成本问题。此外,我们的框架确保公平的激励,并通过b区块链实现分散的外包。最后,我们在以太坊上实现和评估了我们的方案,以证明其可行性和效率。在保持几乎相同的解密成本的情况下,我们的gas使用量在快乐情况下为11×到140×,在挑战情况下为4×到55×,低于Ge等人的方案(TDSC ' 24)在属性数从5到60的情况下。在此基础上,我们展示了其在电动汽车数据共享中的应用,使移动计算资源得到更广泛的利用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blockchain-enabled reliable outsourced decryption CP-ABE using responsive zkSNARK for mobile computing
Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is a promising solution for access control in mobile computing. However, the heavy decryption overhead hinders its widespread adoption. A general approach to address this issue is to outsource decryption to a decryption cloud server (DCS). Existing schemes achieve verifiability but lack an effective exemption mechanism to protect honest DCS from false claims. In this paper, we propose a blockchain-enabled reliable outsourced decryption CP-ABE framework that achieves both verifiability and exemptibility without adding redundant information to the ciphertext. We use zkSNARK to verify outsourced results on blockchain efficiently and introduce a challenge-response mechanism to address the high cost of proof generation. Moreover, our framework ensures fair incentive and enables decentralized outsourcing through blockchain. Finally, we implement and evaluate our scheme on Ethereum to demonstrate its feasibility and efficiency. While maintaining almost the same decryption cost, our gas usage is 11× to 140× in the happy case and 4× to 55× in the challenge case lower than the scheme of Ge et al. (TDSC’24) in attribute numbers from 5 to 60. Building upon the proposed framework, we demonstrate its application in the data sharing of electric vehicles, enabling a more extensive use of mobile computing resources.
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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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