PRIVACY PROTECTION AND INTRUSION AVOIDANCE FOR CLOUDLET-BASED MEDICAL DATA SHARING
European Journal of Molecular & Clinical Medicine,
2022, Volume 9, Issue 3, Pages 10771-10779
AbstractBetter medical care is becoming more necessary as wearable gadgets and cloudlet technologies become in prominence. Data collection, storage, and dissemination, among other things, all fall within the purview of the medical data processing chain. In the traditional healthcare system, sensitive information about patients is often sent to the cloud, which consumes a great deal of energy and has a negative impact on the environment. In the real world, medical data exchange is a crucial and difficult subject. The versatility of the cloudlet is used to create a new healthcare system in this article. Cloudlet's features include data sharing, privacy protection, and intrusion detection. To encrypt user's body data collected by wearable devices, we use the Number Theory Research Unit (NTRU) method first. In order to save energy, this data will be sent to a neighbouring cloudlet in an efficient manner. To assist users identify trustworthy cloudlet partners, we provide a novel trust model that can be applied to the cloudlet. The trust model also facilitates communication between patients with similar illnesses. Third, we separate the medical data of patients stored in the hospital's remote cloud into three sections and safeguard them. At long last, we've developed a novel, collaborative intrusion detection system (IDS) method based on cloudlet mesh to safeguard the healthcare system's big data cloud remotely. The results of our experiments show that the proposed method is effective.
- Article View: 58
- PDF Download: 86