A Medical Privacy Protection Model Based on Threshold Zero-Knowledge Protocol and Vector Space

Recent years have witnessed the rapid development of technologies such as the Internet and the Internet of Things, which have driven the development of all walks of life including economics, medicine, and so on. In the healthcare industry, big data has become a core asset in transforming personal care, and public health, and has been officially incorporated into the national development strategy as a national basic strategic resource. However, privacy security and leakage through medical big data become a serious issue in the healthcare industry, resulting in exploiting details specific to a disease, identity theft, destruction of databases, etc. This study proposes a privacy protection model for medical. data based on threshold zero-knowledge protocol and vector space. The model uses a threshold zero-knowledge protocol to verify the user's identity from the data source. After the verification, the system will vectorize its historical access records to calculate the correlation between their access requests and historical access records. The experimental results show that the model can issue the access permission accurately and reliably, as well as reduce the misjudgment of the system.