K-Anonymous Privacy Preserving Scheme Based on Bilinear Pairings over Medical Data

Recent years have witnessed the advent of technologies such as the Internet of Things, cloud computing, and big data. Also, the analysis and research of data have attracted more and more attention from researchers. For example, the analysis of medical data can help government agencies do right decisions in public health services, or assist medical research institutes in conducting medical research. But it is followed by the privacy preserving of patient medical data in a cloud environment. Our paper proposes a problem-solving scheme that is a k-anonymous privacy preserving scheme based on bilinear pairings (KPSBP) which combines k-anonymity and secure searchable encryption to ensure the patient data privacy is not compromised and the medical data is well shared.