ABSTRACT
The security danger to ever-increasing medical data has been increased by developments in the healthcare industry. Data in the healthcare data management system is large and unstructured since it is recorded in many forms for every patient. For to better handle patient information, a cloud-based healthcare management system may be the best option. Some examples include defamation of prominent patients and medical identity theft. Because of the risks associated with token theft and password forgetting, a biometric based authentication solution is preferable in this case. In this research, we use an improved support vector machine (ISVM) to detect objects and retrieve their attributes. Measures of system resilience include the False Acceptance Rate (FAR) and the False Rejection Rate (FRR). The model’s efficiency is measured in comparison to standard methods. Data in the cloud is much more safe and accessible with the help of the suggested approach.
