Intelligent Medical Multi-Department Information Attribute Encryption Access Control Method Under Cloud Computing

This paper studies the encrypted access control method of smart medical multi-department information attributes in the cloud computing environment. Under the current wave of informatization, smart medical care has become an important development direction of medical services. However, the ensuing information security issues have become increasingly prominent. Especially in the context of cloud computing, information sharing and cooperative work among multiple departments make information security access control particularly important. This article first conducts an in-depth analysis of the characteristics of multi-departmental information in smart medical care. By collecting and sorting out a large amount of medical data, it is found that more than 85% of the data involves patient privacy and core information of medical business, which puts forward extremely high requirements for data confidentiality and integrity. Therefore, we propose an attribute-based encrypted access control method, which realizes differentiated access control for different users and different departments through a fine division of data attributes. In the implementation of the method, we design efficient encryption and decryption algorithms by using the distributed characteristics of cloud computing. Experimental results show that, compared with traditional access control methods, the proposed method improves the efficiency of data processing while ensuring information security, and the average access response time is reduced by about 20%. In addition, we also verified the effectiveness of this method in multi-department information security management of smart medical care through actual case analysis.

@article{Liao2024,
  title     = {Intelligent Medical Multi-Department Information Attribute Encryption Access Control Method Under Cloud Computing},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {11},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Shubin Liao},
  doi       = {10.14569/IJACSA.2024.01511107},
  url       = {https://doi.org/10.14569/IJACSA.2024.01511107}
}