Abstract. In this paper, we provide a secure and e cient encrypted keyword search scheme for multi-user data sharing. Specifically, a data owner outsources a set of encrypted files to an untrusted server, shares it with a set of users, and a user is allowed to search keywords in a subset of files that he is authorized to access. In the proposed scheme, (a) each user has a constant size secret key, (b) each user generates a constant size trapdoor for a keyword without getting any help from any party (e.g., data owner), independent of the number of files that he is authorized to search, and (c) for the keyword ciphertexts of a file, the network bandwidth usage (from the data owner to the server) and storage overhead at the server do not depend on the number of users that are authorized to access the file. We show that our scheme has data privacy and trapdoor privacy. While several recent studies are on secure keyword search for data sharing, we show that they either su↵er from scalability issues or lack user privacy.

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In this paper, a system is proposed which uses blockchain technology in healthcare. In this system, patients can access their health records anytime from anywhere. Moreover, the patients’ health records are put into the blockchain anonymously. Whenever a patient visits a healthcare professional, the authorized entity filters patients’ medical report out by eliminating the patients’ sensitive information. Then, the filtered medical data are put into an off-chain database, while the address of the data is put into the blockchain with an assigned pseudo random identity of the patient. Thus, there are multi pseudo random identities for each patient. Unlike previous studies where the patients’ identities/reports were linkable, in the proposed protocol the patients’ identities are not linkable. The proposed system can also be used to show patients’ health status to some entities when a pandemic happens (e.g. COVID-19). During the COVID-19 pandemic, the patients are required to show their series of vaccinations before they travel internationally/nationally or participate in some social events. To travel or join some events, the patient needs to show only a partial medical history to the security guard without leaking any private information. Furthermore, once the anonymous medical data are put into the off-chain database, the data can be used for data mining and machine learning.