# eHealth Integrity Model Based on Permissioned Blockchain +
## 1 Introduction
### Related Works  
Information security must be taken into account during the design of eHealth systems due to the sensitive nature of medical records. Nowadays, cyberattacks on eHealth systems can impact the basic security properties of medical records, i.e., availability, confidentiality, and integrity. Security requirements for information systems that process medical records are described in ISO TS 18308 [2]. Furthermore, eHealth security is an active research area due to the implementation of new technologies, including cloud technology, Internet-of-Things (IoT) devices, or blockchains, and growing numbers of attacks. [PERSON] et al. [3] reviewed the literature regarding the security and privacy of EHR systems, and identified essentials features for EHR security and privacy. The standards and guidelines related to health-information-system development were analyzed by [PERSON] et al. [4]. The security and privacy requirements for storing medical records in the Cloud from the perspective of healthcare providers and cloud-service providers were analyzed by [PERSON] et al. [5] and by [PERSON] et al. [6]. [PERSON] et al. [5] concluded that storing EHRs in the Cloud means that precautions must be taken to ensure data security. The security of eHealth systems was also discussed by [PERSON] et al. [7]. The problem of key management and authentication in IoT devices working in an eHealth system was reviewed by [PERSON] et al. [8]. They proposed an authentication and key management protocol with support for privilege transfer that is both secure and energy-efficient. Blockchain technology can be used to build new mechanisms that enhance the security of eHealth systems. Blockchains should be used, among other situations (according to Reference [9]), where multiple contributors exist, more trust is required, the need for reliable tracking activity exists, and where data must be reliable over time. For this reason, a blockchain is seen by many as a type of technology that could improve the security of eHealth systems. In eHealth applications, typically permissioned (private) blockchains are used where data are embedded into a blockchain (on-chain storage) or just record hashes are embedded into a blockchain (off-chain storage). For example, [PERSON] et al. [10] proposed the Advanced Blockchain approach, where data are encrypted and stored on-chain (embedded into transactions), [PERSON] et al. [11] proposed MedRec, which is a decentralized record-management system based on a blockchain, and [PERSON] et al. [12] proposed a user-centric health-data sharing solution for mobile environments. In proposals where data are stored on-chain, there is a problem with scalability and efficiency, as many authorized nodes have to get a full blockchain copy. A 2019 study conducted by [PERSON] et al. [13] confirmed that it is possible to exchange EHR data in a private blockchain network, but many improvements are required, including data-size reduction and security issues. Another study, conducted by [PERSON] et al. [14], presented results from testing OmniPHR using a dataset of more than 40,000 patients, achieving an average response time of below 500 ms. In OmniPHR, not all nodes store a complete blockchain copy. Such an approach was used to manage large datasets. A blockchain was used in several other eHealth applications. For example, a private blockchain (Hyperledger Fabric) was used by [PERSON] et al. [15] to ensure the integrity and availability of stored personal health records. They created a tamper-resistant mHealth application that enables cognitive behavioral therapy for insomnia using a smartphone. Next, [PERSON] et al. [16] proposed the MISTore, which is a blockchain-based medical-insurance storage system. A secure EHR system based on blockchain technology and an attribute-based cryptosystem was proposed by [PERSON] and [PERSON] [17]. [PERSON] et al. [18] proposed BeeKeeper 2.0, a confidential blockchain-enabled IoT system using a decentralized outsourcing computation scheme. Lastly, [PERSON] et al.