Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is a promising solution to address the issues of data leakage and sharing in big data. When multiple files are shared, they often have hierarchical access relationships. However, existing hierarchical data CP-ABE schemes can only support simple hierarchical access structures. The limitation arises, necessitating the generation of multiple access structures to meet hierarchical access requirements, resulting in the wastage of computational and storage resources. Therefore, in this paper, we carefully design a dynamic hierarchy access control that allows its level nodes to flexibly participate in the decryption of other nodes, enabling the realization of complex hierarchical data relationships. Building upon this, we construct the Attribute-based Dynamic Hierarchical data Access Control (ADHAC) scheme, achieving efficient and dynamic access control for multiple datasets. Subsequently, we apply our scheme in distributed computing, which enables efficient access control for individuals and institutions over multiple data sets and fine-grained computation. Security analysis indicates that our scheme can resist chosen plaintext attack (CPA). Both theoretical and experimental analyses demonstrate that our scheme has impressive advantages in terms of computational efficiency and storage costs compared to existing schemes.

中文翻译：

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大数据层次结构的动态数据访问控制方案

基于密文策略属性的加密（CP-ABE）是解决大数据中数据泄露和共享问题的一种有前途的解决方案。当多个文件共享时，它们往往具有分层访问关系。然而，现有的分层数据CP-ABE方案只能支持简单的分层访问结构。这就产生了限制，需要生成多个访问结构来满足分层访问要求，从而导致计算和存储资源的浪费。因此，本文精心设计了一种动态层次访问控制，使其层次节点能够灵活参与其他节点的解密，从而实现复杂的层次数据关系。在此基础上，我们构建了基于属性的动态分层数据访问控制（ADHAC）方案，实现了多个数据集的高效动态访问控制。随后，我们将我们的方案应用于分布式计算，这使得个人和机构能够对多个数据集和细粒度计算进行有效的访问控制。安全性分析表明我们的方案可以抵抗选择明文攻击（CPA）。理论和实验分析都表明，与现有方案相比，我们的方案在计算效率和存储成本方面具有令人印象深刻的优势。