Blockchain-Empowered Secure and Privacy-Preserving Health Data Sharing in Edge-Based IoMT

Abstract

Health data sharing, as a booming demand, enables the patients with similar symptoms to connect with each other and doctors to obtain the medical history of patients. Health data are usually collected from edge-based Internet of medical things (IoMT) with devices such as smart wearable devices, smart watches, and smartphones. Since health data are highly private and have great financial value, adversaries ceaselessly launch diverse attacks to obtain private information. All these issues pose great challenges to health data sharing in edge-based IoMT scenarios. Existing research either lacks comprehensive consideration of privacy and security protection or fails to provide a proper incentive mechanism, which expels users from sharing data. In this study, we propose a novel blockchain-assisted data sharing scheme, which allows secure and privacy-preserving profile matching. A bloom filter with hash functions is designed to verify the authenticity of keyword ciphertext. Key-policy attribute-based encryption (KP-ABE) algorithm and smart contracts are employed to achieve secure profile matching. To incentivize users actively participating in profile matching, we devise an incentive mechanism and construct a two-phase Stackelberg game to address pricing problems for data owners and accessing problems of data requesters. The optimal pricing mechanism is specially designed for encouraging more users to participate in health data sharing and maximizing users’ profit. Moreover, security analysis illustrates that the proposed protocol is capable of satisfying various security goals, while performance evaluation shows high scalability and feasibility of the proposed scheme in edge-based IoMT scenarios.

A privacy‐preserving model for blockchain‐based data sharing in the industrial internet

“…The additional cost was about 47 USD, and according to formula (17), the total cost of industrial production should be 427 USD. In contrast, the p should be 494 USD and more than 558.4 USD according to formulas (20) and (18), respectively. The above analysis shows that if P is higher than 558.4 USD, the data sharing scheme and the privacy-preserving model will have a positive influence on industrial benefits.…”

“…Islam 19 implemented pandemic monitoring using the Internet of Drone Things based on blockchain, which has obvious advantages in security and reliability. Nie 20 built a data sharing model for the medical Internet of Things based on blockchain, it can effectively protect data privacy. In addition to the Internet of Things, in the field of artificial intelligence and federal learning, blockchain can effectively support the key issue of model sharing.…”

Blockchain-based Federated Learning for Industrial Metaverses: Incentive Scheme with Optimal AoI

“…To motivate users for sensing data sharing, some efforts have been conducted [10]- [12]. However, most works only consider a complete information scenario and ignore the problem of information asymmetry.…”

“…Therefore, it is necessary to design a user-centric incentive mechanism for incentivizing users with fresh data in healthcare metaverses. Some efforts have been conducted for incentivizing users with data sharing [10]- [12], but they ignore data freshness and the problem of information asymmetry.…”

Probabilistic data structures in smart city: Survey, applications, challenges, and research directions

“…Similarly, Nie et al propose a secure and privacy-preserving blockchain-based data-sharing scheme. For secure profile matching, the 'Key-policy attribute-based encryption' algorithm is used, and to verify the authenticity of ciphertext, a bloom filter with hash functions is designed [200].…”