###### Abstract  
Due to the value and importance of patient health records (PHR), security is the most critical feature of encryption over the Internet. Users that perform keyword searches to gain access to the PHR stored in the database are more susceptible to security risks. Although a blockchain-based healthcare system can guarantee security, present schemes have several flaws. Existing techniques have concentrated exclusively on data storage and have utilized blockchain as a storage database. In this research, we developed a unique deep-learning-based secure search-able blockchain as a distributed database using homomorphic encryption to enable users to securely access data via search. Our suggested study will increasingly include secure key revocation and update policies. An IoT dataset was used in this research to evaluate our suggested access control strategies and compare them to benchmark models. The proposed algorithms are implemented using smart contracts in the hyperledger tool. The suggested strategy is evaluated in comparison to existing ones. Our suggested approach significantly improves security, anonymity, and monitoring of user behavior, resulting in a more efficient blockchain-based IoT system as compared to benchmark models. Security; blockchain; privacy; homomorphic encryption; deep learning; access control; smart contracts 202  
In industrial applications, healthcare is considered to be a vital field. In addition to a classic medical diagnosis, patients' body parameters, comprised of heart rate, blood sugar level, electroencephalogram, and additional vital biomedical signals can be monitored by integrating numerous medical sensing devices for diagnosis [3], as well as health quality improvement. Medical diagnosis, biomedical research, and policy making sharing can provide easiness in sharing and secure access. The Internet of Things (IoT) has been proposed to enhance quality of the industries, break regional limitations to achieve remote monitoring, perform autonomous production and deliver real-time information to the end users. For instance, the healthcare industry can often take advantage of the IoT, where industrial sensors and actuators are used as wearable devices to collect users' physiological data, such as blood pressure, electrocardiogram (ECG), temperature, and so on. These physiological data are usually sent to the nearby devices or servers of the user to carry out further data collection, aggregation, and then sent for diagnosis and input to a industrial provider using an open channel, i.e., the Internet. However, due to the round-the-clock networking of nodes in this IoT network, it is vulnerable to various security issues, such as message tampering, eavesdropping, and denial of service (DoS) attacks. In the industrial industry, this raises major security issues as the misuse of data can result in incorrect diagnosis and can cause life-threatening scenarios for the patients under observation. For instance, a clinician may want to access the medical records of a patient located in different hospitals databases in order to decide for the best treatment of a patient. Moreover, this market can bring a huge and positive impact on the economy. In a nutshell, the digital healthcare systems' data sharing and trust are key factors for success, and deficiency could result in distrust among patients towards the e-healthcare market [4]. There exist several searchable encryption (SE) methods to provide solution to the problems as mentioned above, but they are not as efficient regarding flexibility and anonymity. SE can be categorized into different types based on several parameters such as single write (SW), multiple write (MW) single read (SR), and multiple read (MR) strategies. However, all SE approaches are not as efficient when deploying to the cloud or server-based architecture systems.