## 1 Introduction
[11] introduced the first CP-ABE system in 2007, embedding the access tree structure within ciphertext; however, it is challenging to deploy in practice. [PERSON] et al. [12] built on [PERSON] et al. 's work in the following year and proposed a CP-ABE system with an efficient general access structure while also proving selection security under the standard model. In 2012, [PERSON] and [PERSON] [13] developed a broad strategy for converting the standard model's concept of selection security into adaptive security. In today's cloud computing, CP-ABE has a significant influence. In 2015, [PERSON] et al. [14] proposed a traceable and auditable CP-ABE scheme in cloud computing to address key abuse by dishonest users in the cloud storage environment [15], but it does not provide key revocation. [PERSON] et al. [16] proposed a traceable and undeniable CP-ABE scheme based on [PERSON]'s work to solve the problem of semi-honest institutions illegally selling keys. Under the big data environment [17], data can be used to verify the validity of the protocol [18] and can also be used to train the robot [19]. However, these web data have no real ownership. [PERSON] et al. [20] investigated the basic challenges surrounding data confirmation in 2016. [PERSON] et al. [21] presented a service system to defend the property rights of personal data in 2017. [PERSON] et al. [22] suggested a large data correct confirmation technique based on blockchain technology in the same year, but the issue is  
Figure 1: The principle of encryption and decryption of CP-ABE. that the data source cannot be verified. In 2018, [PERSON] and his colleagues [23] introduced a novel approach for verifying big data using blockchain and digital watermarking technology, but the authority agency can access the data owner's source data. Although this solution can be applied to the environment of cloud storage, due to the limitation of its form of plaintext confirmation, the privacy of users cannot be guaranteed. [PERSON] et al. [24] developed a smart contract-based big data property right confirmation system the following year. In 2021, [PERSON] et al. [25] proposed a data ownership confirmation scheme based on consortium blockchain in IoT environments [26], with a focus on controlling the flow of data. However, the scheme cannot be applied to one-to-many environments such as cloud storage. Professors [PERSON] and [PERSON] from Tsinghua University announced their plans to develop an innovative solution for managing large-scale data transactions. Their approach involves leveraging cutting-edge cryptography techniques and advanced mechanisms for economic design to create a robust and effective system for processing and exchanging data. By combining these two technologies, they aim to address the unique challenges associated with managing and securing large volumes of data, ultimately providing a reliable and efficient solution for businesses and organizations worldwide. This technique assures data transaction security while also increasing transaction efficiency. In 2022, [PERSON] et al. [27] proposed a data ownership confirmation scheme based on the Ethereum blockchain and smart contracts. The parties authenticate their identities through a protocol for generating data fingerprints based on smart contracts. However, the article did not address the issue of user privacy protection on the public blockchain. Based on the research status above, we propose a new data confirmation scheme in the cloud storage environment, focusing on user privacy protection and preventing the leakage of original plaintext data. The scheme can effectively protect the privacy of data owners while ensuring data confirmation, and in the process of confirmation, no one can access plaintext, thus reducing the risk of data leakage. We embed the data owner's identification information into CP-ABE using Paillier encryption and change the plaintext confirmation form to the ciphertext confirmation form. An audit phase is introduced at the end of the confirmation process.