# Secure PBFT Consensus-Based Lightweight Blockchain for Healthcare Application
## 2 Literature Review
[23] proposed Fusion Chain, a decentralized lightweight blockchain for IoT devices that resolves the storage issue, data privacy, and high computational requirement of blockchain by implementing an interplanetary file system (IPFS), PBFT consensus algorithm, and public-key encryption using PKI. The proposed model was written in Node.js and Golang. The experimental results demonstrated improved performance of the system resolving data reliability issues and security vulnerabilities of IoT applications caused by Mirai botnet and DDoS attacks. Furthermore, the proposed model can be improved to achieve high TPS. For efficient data management in a blockchain environment, [PERSON] [24] proposed a modified-pBFT algorithm, where a group of leader nodes is selected for the consensus operation. The proposed model simplifies the request management process and reliable leader node election process. Experimental results show better performance in TPS and network communication cost compared to PBFT, but accurate evaluation techniques are required for the reliability of nodes. More interestingly, the authors [PERSON] et al. [25] designed a lightweight blockchain using a reward and punishment strategy-based PBFT consensus algorithm and Joint Delay Storage Cost Minimization algorithm for storage optimization. The existing PBFT was compared with the proposed model using Hyperledger Caliper. Improved consensus throughput and reduced delay and communication times are recorded. [PERSON] et al. [26] proposed an energy-efficient consensus algorithm for IoT-blockchain-based applications. The proposed algorithm uses the modified PBFT consensus by implementing VRF to choose consensus nodes, ensuring the security of the primary node. Although the simulation results in improved performance in terms of latency and energy consumption compared to the existing PBFT algorithm, it decreased throughput when the number of nodes increased. [PERSON] et al. [27] proposed a Dynamic Reputation Practical Byzantine Fault Tolerance (DPBFT) algorithm by implementing a credit-based consortium method for the consensus node election process, which involves a monitoring node that divides the node-set based on the reputation value. The proposed algorithms resolve the issues of traditional PBFT in terms of a long consensus period, low efficiency, and high CPU usage, but the entire process of DPBFT is managed by the monitoring node. Furthermore, the DBPFT can be improved by implementing clustering techniques. Accomplishing good performance in terms of throughput and scalability without compromising the security is a challenging task in all IoT applications. [PERSON] et al. [28] introduced the Security-Aware Genetic Algorithm-based Practical Byzantine fault Tolerance scheduler for balancing the security requirements and overhead caused during the block creation by assigning a security level to each transaction based on the requirements. The proposed model was tested in a simulation environment; although the experimental result shows better performance compared to the traditional PBFT, the model cannot be used for blockchain having fewer transactions. Table 2 illustrates the various existing works on PBFT consensus, compared based on three different parameters such as security, privacy, and communication overhead considering scale as least considered (LOW), moderately considered (MID), and (highly considered) HIGH.