A Hospital Appointment System Based on Privacy Protection
With the rapid development of information technology, the user privacy and data security of hospital appointment systems are becoming increasingly important. Medical data contains sensitive content such as personal health information and diagnosis and treatment records, which, once leaked, may seriously damage the privacy and security of patients. The causes of data breaches include improper access control, cyber attacks, storage system vulnerabilities, and improper handling of data by partners. How to prevent data leakage effectively has become the key direction of medical data privacy protection research. This paper aims to design and implement a hospital appointment system based on privacy protection, using DES encryption algorithm, LSB image steganography algorithm and MD5 salt algorithm to implement management, reservation, encryption and steganography functions for administrators and users based on Java web. The administrator system provides management functions for hospital resources and appointment status. To ensure data security, the system uses MD5 salt encryption algorithm to encrypt and store privacy information in the database. The user system provides users with convenient and fast appointment services. In order to protect user privacy, the system adopts DES encryption algorithm and LSB image steganography method to encrypt and steganize user registration and medical information. This system not only implements basic hospital appointment functions, but also fully considers user privacy and data security. The advantage and novelty of this scheme is that it can protect the privacy of the user’s medical data, make the user’s private data invisible ciphertext form, and embed it in the picture to eliminate steganography during the transmission process, so as to realize the safe transmission and storage of the data.
Authors
- Shuang‐Nan Zhang (ORCID: https://orcid.org/0000-0001-5586-1017)
- Jun Ye (ORCID: https://orcid.org/0000-0003-1010-2484)
Institutions
- Hainan University (CN)
Publication Details
- Journal
- Procedia Computer Science
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.procs.2025.04.026
- Primary Topic
- Recommender Systems and Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00