An Intuitionistic Fuzzy based Intelligent System for Semantic Interoperability and Privacy Preservation in Healthcare Systems

Secure semantic interoperability solutions are required in the age of the digital era as heterogeneous IoT medical devices increase, and these devices produce vast amounts of data daily. Since the data is enormous, the hospital could not keep the complete data collection on its hospital information server. The cloud often handles storage, and state-of-the-art privacy protection relies on reliable cloud servers. Even if the documents are encrypted, the server may still determine what is contained there. This study ensures healthcare data privacy using AES and ElGamal encryption techniques while maintaining semantic Interoperability. The suggested technique provides a mechanism for document decryption on the customer’s end. By the amalgamation of medical ontology UMLS and Intuitionistic Fuzzy logic, most linguistic issues, such as word sense disambiguation, identification of lexical variances, hypernymy-hyponymy issues, and meronymy-holonymy issues, are addressed in this work. Results show that the proposed method outperforms existing solutions.