Revocable-Hierarchical-Identity-Based Inner Product Function Encryption in Smart Healthcare
With the development of cloud computing and the digital transformation of the medical industry, the application scenarios and effects of smart healthcare are constantly expanding and improving. Smart healthcare plays an important role in improving service quality and medical efficiency and reducing medical costs. However, in the process of data collection, storage, and transmission, the risk of patients’ privacy being illegally accessed or leaked has become increasingly prominent. These medical data contain sensitive information about patients, and once leaked, it will violate the privacy of patients, cause medical accidents, and seriously damage the legitimate rights and interests of patients. An efficient and reliable privacy protection mechanism is the foundation and key to establishing a harmonious doctor-patient relationship and improving medical quality. Although traditional encryption methods can provide certain information security protection, they cannot balance data protection and data analysis and processing and are not suitable for intelligent medical environments that require more precise medical decisions. Therefore, we propose a hierarchical identity-based inner product functional encryption scheme with a malicious user revocation mechanism aimed at addressing the privacy and security issues of patients in smart healthcare. This solution allows specific access and analysis of data while ensuring that patients’ sensitive information is protected from infringement, enabling doctors to diagnose and treat more accurately and optimize the allocation of medical resources to the greatest extent possible. Furthermore, we have formally demonstrated the security of the scheme and conducted a security analysis and performance comparison. The results show that our solution has better performance while ensuring security and is suitable for the efficient and secure data processing requirements of smart healthcare.
Authors
- Bo Yang (ORCID: https://orcid.org/0000-0002-0419-1209)
- Yanwei Zhou (ORCID: https://orcid.org/0000-0002-7254-3579)
- Mingwu Zhang (ORCID: https://orcid.org/0000-0001-8551-8826)
- Jing Wang (ORCID: https://orcid.org/0000-0002-0610-4308)
- Yasi Zhu
Institutions
- Sichuan University (CN)
- Hubei University of Technology (CN)
- Shaanxi Normal University (CN)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2025-01-09
- DOI
- https://doi.org/10.1109/jiot.2025.3527556
- Citations
- 2
- Primary Topic
- Patient Dignity and Privacy
- Type
- article
- Field-Weighted Citation Impact
- 3.76
Funders
- National Natural Science Foundation of China