A Cloud-Based Privacy Preserving e-Healthcare System Using Whale Optimization

Internet is an integral part of our daily lives attributable to its increasing usage. During this model, users can impart their information and communicate with others through social communities. The e-healthcare community service considerably resolves the problems of individual patients that are remotely located, have uncomfortable medical conditions, or have caretaker responsibilities which are able to proscribe them from obtaining comfortable medical and emotional support. Participation in online social collaborations might not be straightforward because of cultural and language barriers. This paper proposes a privacy-preserving cooperative e-healthcare system that divides patients or caretakers into totally different groups. This technique permits patients or caretakers to talk with different patients with similar issues, perceive their feelings, and share several problems with their own. However throughout this method, personal and sensitive information can not be disclosed to anyone at any purpose of your time. The suggested model uses a special technique, called minmax whale optimization to cluster e-profiles based on their similarities. Finally, clustered profiles are encrypted by exploiting distributed hashing technique to preserve patients’ personal info. The results of planned framework are compared with famous privacy-preserving algorithms of clustering by using accepted similarity measures.