At present, the world has been changing tremendously. China is accelerating the construction of a new development pattern in which its big domestic cycle is the subject, and the domestic and international double cycles promote each other. As the core support of the digital society, the cloud platform will become a significant focus of opening up the “double cycles”1. As an important link, the cloud platforms have developed rapidly in various fields such as the internet, government affairs, finance, transportation, logistics, and education, accelerating the implementation of “all cloud services all services cloudification” and fully empowering urban governance modernization and high-quality economic development. Big data has penetrated every industry and business functional area and has become an influential production factor2. Cloud computing and big data have made the entire society increasingly dependent on science. In the era of big data, “cloud government affairs” depending on big data has become a new model of social governance. Big data has become a key target of network attacks due to its huge value and centralized storage management mode. Blackmail attacks and data leakage problems in big data are becoming increasingly serious3. Data concentration leads to a greater impact on internal leakage risks, data distribution leads to a greater impact on external leakage risks, and an increase in data-associated personnel will also cause greater risk problems4. He et al. pointed out that with the increasing demand for data sharing in the era of big data, user data cannot be better protected, and user privacy is at risk of leakage because the data shared by users on the internet depend on third-party platforms5. As of now, many studies about data privacy protection have been reported; however, these research results are difficult to apply into subdivided fields6. Therefore, the access control and protection of data have become scientific problems that need to be solved urgently.
Patent data contain user privacy. The current policy results in that each patent submission and review involves private information, such as the certificate number, telephone number, and detailed address of the applicants. Second, the patent data also contain key technological innovation information before its disclosure. Thus, leakage will cause significant loss of interest to the applicants; in the meantime, patent review conclusions and invalid information on reexamination also involve significant interests of relevant parties7. Joung and Kim pointed out that the current internal protection of patent data lay in the development of a new generation of patent review and retrieval systems, which greatly improved the security of patent data access by adding cloud computing and big data processing methods8. Bhattarai et al. suggested that the small number of national intellectual property bureaus and effective processing capacity often led to longer processing and review of patent data. Therefore, while adopting traditional data access security, not only should protecting the security and privacy of data storage focused but the distributed deployment should also be supported while ensuring performance and security. In this way, the efficiency of patent review could be improved9. In particular, the continued development of the review centers will place higher requirements on the data processing functions and access speed of the patent review systems with examiners all over the country10. Such a trend requires a new patent review system that can quickly distribute processing and protect data privacy.
Therefore, a scheme strategy based on data fragmentation and encryption is proposed based on studying the structure of the traditional patent review systems. This scheme uses blockchain technology to store the patent information data in different block nodes after data fragmentation. The innovation is that the encryption algorithm is used to process the privacy of patent data and content, and the hierarchical storage of data is realized. On this basis, safe and effective patent data is constructed to protect the scheme. This provides a research basis and practical value for the protection and review of patent data.
There are five sections in total. The first section is the “Introduction”, in which the importance of data access control and protection and the problems in patent data protection are put forward, and the research ideas are determined. The second section provides a “Literature review”, in which the research framework is clarified according to the development of patent information, classification and characteristics of patent data, the requirements for patent data security in the new stage, and the current research progress. The third section introduces the Research methodology, in which the data fragmentation and encryption algorithm involved are explained, the corresponding storage and encryption model is proposed, and the data access control and protection model is constructed based on patent technology. The fourth section is the “Results and discussions”, in which the proposed model is analyzed using examples. The model’s safety performance and the algorithm’s advantages are summarized, and the proposed scheme is compared with the method proposed in the previous research. The fifth section is the “Conclusion”, in which the key results, actual contributions, limitations, and prospects are illustrated.
