在云中通过访问控制和范围查询进行安全的多维数据检索

IF 3 2区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Zhuolin Mei , Jin Yu , Caicai Zhang , Bin Wu , Shimao Yao , Jiaoli Shi , Zongda Wu
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引用次数: 0

摘要

将数据外包到云端具有各种优势,如提高可靠性、增强灵活性、加快部署速度等。然而,恶意攻击和内部滥用权力等潜在威胁会导致数据泄漏,从而引发数据安全问题。数据加密是解决这些问题的公认方案,即使在发生泄密事件时也能确保数据的机密性。然而,加密数据给访问控制和范围查询等常见操作带来了挑战。为了应对这些挑战,本文提出了具有访问控制和范围搜索功能的云安全多维数据检索(SMDR)。本文提出的 SMDR 策略同时支持访问控制和范围查询。SMDR 策略的设计巧妙地利用了桶的最小点和最大点,使 SMDR 策略非常适合支持多维数据的范围查询。此外,我们还对基于密文策略属性的加密(CP-ABE)进行了修改,以便与 SMDR 策略有效集成,然后利用 SMDR 策略和 CP-ABE 构建了一个安全索引。利用安全索引,可以有效支持对加密多维数据的访问控制和范围查询。为了评估 SMDR 的效率,我们进行了大量实验。实验结果证明了 SMDR 在处理加密多维数据方面的有效性和适用性。此外,我们还对 SMDR 进行了详细的安全性分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Secure multi-dimensional data retrieval with access control and range query in the cloud

Outsourcing data to the cloud offers various advantages, such as improved reliability, enhanced flexibility, accelerated deployment, and so on. However, data security concerns arise due to potential threats such as malicious attacks and internal misuse of privileges, resulting in data leakage. Data encryption is a recognized solution to address these issues and ensure data confidentiality even in the event of a breach. However, encrypted data presents challenges for common operations like access control and range queries. To address these challenges, this paper proposes Secure Multi-dimensional Data Retrieval with Access Control and Range Search in the Cloud (SMDR). In this paper, we propose SMDR policy, which supports both access control and range queries. The design of the SMDR policy cleverly utilizes the minimum and maximum points of buckets, enabling the SMDR policy is highly appropriate for supporting range queries on multi-dimensional data. Additionally, we have made modifications to Ciphertext Policy-Attribute Based Encryption (CP-ABE) to enable effective integration with the SMDR policy, and then constructed a secure index using the SMDR policy and CP-ABE. By utilizing the secure index, access control and range queries can be effectively supported over the encrypted multi-dimensional data. To evaluate the efficiency of SMDR, extensive experiments have been conducted. The experimental results demonstrate the effectiveness and suitability of SMDR in handling encrypted multi-dimensional data. Additionally, we provide a detailed security analysis of SMDR.

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来源期刊
Information Systems
Information Systems 工程技术-计算机:信息系统
CiteScore
9.40
自引率
2.70%
发文量
112
审稿时长
53 days
期刊介绍: Information systems are the software and hardware systems that support data-intensive applications. The journal Information Systems publishes articles concerning the design and implementation of languages, data models, process models, algorithms, software and hardware for information systems. Subject areas include data management issues as presented in the principal international database conferences (e.g., ACM SIGMOD/PODS, VLDB, ICDE and ICDT/EDBT) as well as data-related issues from the fields of data mining/machine learning, information retrieval coordinated with structured data, internet and cloud data management, business process management, web semantics, visual and audio information systems, scientific computing, and data science. Implementation papers having to do with massively parallel data management, fault tolerance in practice, and special purpose hardware for data-intensive systems are also welcome. Manuscripts from application domains, such as urban informatics, social and natural science, and Internet of Things, are also welcome. All papers should highlight innovative solutions to data management problems such as new data models, performance enhancements, and show how those innovations contribute to the goals of the application.
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