## 4 Findings
### Healthcare  
Dealing with big data in the healthcare domain can raise security and privacy issues, endangering the patient's life. A novel privacy-preserving framework to secure the analysis and management of healthcare data is proposed [99]. This study addresses the IoT devices' constraints and how to resolve the issues requiring extra computational power, high bandwidth, and computation cost. The proposed framework consists of healthcare wearable IoT devices, smart contracts, healthcare providers, cloud storage, and an overlay network. Asymmetric and ARX symmetric encryption schemes are both used. Signature correctness and signers' anonymity are achieved using lightweight ring signature technology. Further work can be completed to implement this framework in a testable environment and provide more security guarantees. BIoTHR [100] is an EHR management system based on private blockchain to ensure the timely monitoring of reliable and secure data transmission. This scheme supports full EHR utilization, a swarm exchange network for IoT-based implementation, UML activity modeling, and trusted parties. Five sensor nodes are employed to aggregate patient information to provide the network with heterogeneous features. The authors included a detailed discussion of a novel swarm exchange paradigm to create a tamper-proof and robust system. Different algorithms were used to create the private blockchain, swarm listening, address announcement of swarm interface listening, swarm connection opening, and connection closing. This study provides protection of data privacy, protection against fraud, security and transparency, interoperability, access control, pseudonymity, full decentralization, high availability, design simplification, and reduced cost. This design can be improved to function in a large-scale network, API is required, and a proper manner of mining is needed. Another study that addresses access control is proposed using blockchain architecture for e-health applications [101]. The general blockchain structure was modified to make this approach fit the healthcare domain, reduce data redundancy by clustering network miners, and reduce transaction size to reduce network overhead; a pseudonym is assigned for each patient, and the data are stored in the nearest location to address security and privacy challenges. This model consists of sensors, Personal Digital Assistance (PDA) or a smartphone, the IoT Health Manager (HHM), a central server responsible for managing the data, healthcare institutions, a blockchain network, and miners. Further implementation and experiments are required to evaluate this model. To eliminate the issue of large-scale networks, Healthchain [102] is a privacy-preserving scheme proposed for large-scale health data to achieve fine-grained access control. This scheme consists of IoT devices, user nodes, doctor nodes, accounting nodes, storage nodes, Userchain, and Docchain. This design aims to provide high efficiency, privacy preservation, accountability, and on-demand revocation. The blockchain network (referred to as Healthchain in this design) is divided into Userchain and Docchain (called subblockchains). Userchain is implemented to prevent tampering with users' transactions; it contains IoT transactions and key transactions. Diagnostic transactions are the only ones supported by Docchain and are secured by the diagnostic key assigned to each user. Keys were decoupled from encrypted data to make key management more flexible. In order to protect users' privacy, they can revoke doctors' access to their records at any moment. This scheme provides privacy preserving, accountability, and revocability. This study meets the standard security criteria according to its security analysis. The performance evaluation results suggest that Healthchain is a feasible and efficient solution. Pseudonym-Based Encryption with Different Authorities (PBE-DA) [103] is a novel protocol that allows patients to manage their EHR data securely and provide the perfect privacy preserving.