## 2 Related Works  
[PERSON] et al. [11] present a DL framework based on BC that offers a dual level of security and privacy. Initially, a BC technique was modelled in which each participating entity was verified, validated, and registered by making use of a smart contract related enhanced proof-of-work to reach the target of privacy and security. Then, a DL approach including bidirectional long short-term memory (BLSTM) for a variational autoencoder (VAE) and intrusion detection systems for privacy were devised. [PERSON] et al. [12] introduced BloMT, a BC Hyperledger fabric-assisted consortium architecture which offers transparency, security, and integrity to health-oriented transactions and interchanges delicate medical data in serverless peer-to-peer (P2P) secured network settings. A consensus was devised and constituted to decrease rate of BC resource limitations on the IoMT. In [13], suggesting a BC-based secured data management framework (BSDMF) for medical data related to the IoTs to exchange patients' data securely and improve data accessibility and scalability. To assure data management and data transmission security among associated nodes, the IoMT-related security structure uses BC. In [14], this study evaluated offloading and scheduling issues for medical workflow in IoMT fog-cloud platforms. Thus, this study addressed the issue as an offloading and scheduling issue and developed deep reinforcement learning (DRL) as a Markov problem. This study designed an innovative DRL and BC-based system which contained multi-criteria offloading depending on DRL policies. [PERSON] et al. [15] developed an LSEOS method called lightweight secure efficient offloading scheduling. LSEOS has lightweight and secured offloading and scheduling methodologies whose offloading delay will be lesser compared to prevailing techniques. The end goal of LSEOS is to run the application over other nodes and diminish the delay and security threats in the mechanism. The metaheuristic LSEOS has the elements they are scheduling with neighbourhood search schemes, adaptive deadlines, and sorting. [PERSON] and [PERSON] [16] offered an innovative contract-based consortium BC technique. The authors compiled interplanetary file systems (IPFS) and cluster nodes where smart contracts are deployable in the early phase. The IPFS cluster node assures the authentication and security of gadgets and even offers safe storage in IoMT based health care systems. [PERSON] et al. [17] designed DL with BC-based secured image transmission and diagnosis system for the IoMT environment. The elliptic curve cryptography (ECC) was implemented in the initial stage, and then by combining grasshopper and fruit fly optimization (GO-FFO) system, ECC's optimum key generation is taken. Finally, a method called a deep belief network (DBN) is applied to find the existence of disease. In [18], a novel secure authentication method utilizing ML was presented. To find the attack authentication and detection in an IoMT platform, this study applies ML and k-nearest neighbour (KNN) with smart contract (KNN-MLSC). [PERSON] et al. [19] proposed an interplanetary file system (IPFS) enabled model for secure healthcare system. It enables the client to continuously upload the healthcare information gathered by IoT devices and to add to the BC transactions. The authors in [20] developed a BC based electronic medical records (EMR) management model for a smart healthcare system. The privacy of the healthcare data can be accomplished using BC technology. It offers off-chain storage for the records and assuring the authenticity and integrity of the health records. In [21], a new hybrid Elman Neural-based Blowfish BC approach has been introduced for the security of the healthcare data in the IoT environment. The Elman network offered continual monitoring to predict abnormal activities in the trained multimedia data. The authors in [22] developed a Lionized Golden Eagle based Homomorphic Elapid Security (LGE-HES) technique with blockchain in healthcare network.