Nowadays, an increasing amount of data has been sent to the cloud for analysis and storage, and data security in the cloud has been widely concerned. Among them, CP-ABE is regarded as one of the most promising technologies to protect outsourced data. However, in most CP-ABE schemes, attackers may obtain user privacy information from policy plaintext. More likely, partial policy hiding programme neither satisfies full policy hiding nor applies to the needs of the large universe. In this paper,we hide both attribute values and names in policy by using private set intersection (PSI). The CP-ABE programme not only supports a complete hiding policy, but also can calculate the authorization relationship and mapping relationship between user passwords and keys. We use a polynomial-based PSI and a recursive algorithm to calculate the authorization relationship. And with the help of the algorithm and the label vector, the mapping is determined under communication restrictions. Through the outsourcing index, we achieve an efficient hiding strategy and effectively reduce the user's computing overhead. Finally, theoretical analysis and experiments show that our model has better performance while effectively protecting sensitive attributes.

如今，越来越多的数据被发送到云端进行分析和存储，云端的数据安全受到广泛关注。其中，CP-ABE被认为是最有前途的外包数据保护技术之一。然而，在大多数 CP-ABE 方案中，攻击者可能会从策略明文中获取用户隐私信息。更有可能的是，部分策略隐藏程序既不能满足完全策略隐藏，也不能适用于大宇宙的需求。在本文中，我们通过使用私有集合交集 (PSI) 在策略中隐藏属性值和名称。CP-ABE 程序不仅支持完整的隐藏策略，还可以计算用户密码和密钥之间的授权关系和映射关系。我们使用基于多项式的 PSI 和递归算法来计算授权关系。并且在算法和标签向量的帮助下，在通信限制下确定映射。通过外包索引，我们实现了高效的隐藏策略，有效降低了用户的计算开销。最后，理论分析和实验表明，我们的模型在有效保护敏感属性的同时具有更好的性能。