Search

The advancements and adoption of cloud-assisted ehealthcare systems have enabled the storage of massive electronic medical records (EMRs) in the cloud for efficient and easy access. A direct benefit of EMRs is the ability of patients to search for EMRs that are similar to their own in the cloud for use as references. These similar EMRs can help a patient find appropriate medical services quickly. However, for large-scale ehealthcare systems, challenges remain with respect to ensuring the efficiency and privacy of these queries. In this study, we construct an efficient and privacy-preserving similar EMR query scheme to help patients find similar EMRs to reference in a large-scale ehealthcare system. Specifically, we propose a coarse-grained query method based on a binary decision tree to find a set of EMRs corresponding to the patient's set of medical-symptom keywords. We also design a fine-grained query method to find similar EMRs that meet the threshold set by the patient. A detailed security analysis shows that the proposed scheme is secure. The efficiency of the proposed method in a large-scale ehealthcare system is verified experimentally. • An efficient and privacy-preserving similar EMRs query scheme is proposed. • A novel privacy-preserving health symptom keywords match query protocol is designed. • Security analysis demonstrates the security of the proposed scheme. • Experimental simulations show the efficiency of the scheme. [ABSTRACT FROM AUTHOR]

With rise of 5G/6G network, low-storage devices usually outsource data for higher rate and less latency. Non-controlled outsourcing and complex communications incur security issues for IoT applications. Specially, user privacy and access reliability pose technical challenges for sensitive data outsourcing and sharing. In this paper, we harmonize functional encryption and blockchain to propose a r eliable and p rivacy-aware a ccess c ontrol system named R-PAC. It allows a result-form access without learning raw information and fair interaction against malicious users. With a combination of all-or-nothing encapsulation technology, R-PAC supports users' dynamic joining and key leakage resistance. We design R-PAC from Boneh–Franklin identity-based encryption, with forward-coverable encryption and reverse-discoverable decryption, and formally prove its indistinguishability security. We implement a R-PAC prototype and deploy it to a simulated Ethereum network to evaluate its performance. Experiments from both data access and transaction overhead show that R-PAC is with reasonable cost and has a trade-off between efficiency and strong security/functionality. • We propose R-PAC, a reliable and privacy-aware access control system. • We design R-PAC from Boneh–Franklin IBE, and formally prove its IND security. • We implement a R-PAC prototype and deploy it to a simulated Ethereum network. [ABSTRACT FROM AUTHOR]

• A Privacy-preserving contact Tracing scheme in 5G-integrated and Blockchain-based Medical applications, named PTBM, is proposed. • Everyone can perform location checking with his mobile phones to find whether they have been in possible contact with a diagnosed patient without violating their privacy. • A trusted medical center can effectively trace the patients and their corresponding close contacts. • Security and performanc e analysis show that the proposed PTBM scheme achieves privacy protection, traceability, reliability, and authentication, with high efficiency and low latency. The current pandemic situation due to COVID-19 is seriously affecting our daily work and life. To block the propagation of infectious diseases, an effective contact tracing mechanism needs to be implemented. Unfortunately, existing schemes have severe privacy issues that jeopardize the identity-privacy and location-privacy for both users and patients. Although some privacy-preserving systems have been proposed, there remain several issues caused by centralization. To mitigate this issues, we propose a P rivacy-preserving contact T racing scheme in 5G-integrated and B lockchain-based M edical applications, named PTBM. In PTBM, the 5G-integrated network is leveraged as the underlying infrastructure where everyone can perform location checking with his mobile phones or even wearable devices connected to 5G network to find whether they have been in possible contact with a diagnosed patient without violating their privacy. A trusted medical center can effectively trace the patients and their corresponding close contacts. Thorough security and performance analysis show that the proposed PTBM scheme achieves privacy protection, traceability, reliability, and authentication, with high computation & communication efficiency and low latency. [ABSTRACT FROM AUTHOR]