The IoT refers to the interconnection of things to the physical network that is embedded with software, sensors, and other devices to exchange information from one device to the other. The interconnection of devices means there is the possibility of challenges such as security, trustworthiness, reliability, confidentiality, and so on. To address these issues, we have proposed a novel group theory (GT)-based binary spring search (BSS) algorithm which consists of a hybrid deep neural network approach. The proposed approach effectively detects the intrusion within the IoT network. Initially, the privacy-preserving technology was implemented using a blockchain-based methodology. Security of patient health records (PHR) is the most critical aspect of cryptography over the Internet due to its value and importance, preferably in the Internet of Medical Things (IoMT). Search keywords access mechanism is one of the typical approaches used to access PHR from a database, but it is susceptible to various security vulnerabilities. Although blockchain-enabled healthcare systems provide security, it may lead to some loopholes in the existing state of the art. In literature, blockchain-enabled frameworks have been presented to resolve those issues. However, these methods have primarily focused on data storage and blockchain is used as a database. In this paper, blockchain as a distributed database is proposed with a homomorphic encryption technique to ensure a secure search and keywords-based access to the database. Additionally, the proposed approach provides a secure key revocation mechanism and updates various policies accordingly. As a result, a secure patient healthcare data access scheme is devised, which integrates blockchain and trust chain to fulfill the efficiency and security issues in the current schemes for sharing both types of digital healthcare data. Hence, our proposed approach provides more security, efficiency, and transparency with cost-effectiveness. We performed our simulations based on the blockchain-based tool Hyperledger Fabric and OrigionLab for analysis and evaluation. We compared our proposed results with the benchmark models, respectively. Our comparative analysis justifies that our proposed framework provides better security and searchable mechanism for the healthcare system.

In the era of smart healthcare, Internet of Medical Things (IoMT)-based Cyber-Physical Systems (CPS) play an important role, while accessing, monitoring, assessing, and prescribing patients ubiquitously. Efficient authentication and secure data transmission are the influential impediments of these networks that need to be addressed to maintain credence among clients, healthcare specialists, pharmacologists, and other associated entities. To address the authentication and data privacy issues in smart healthcare, in this paper we propose a lightweight hybrid deep learning protocol to achieve security and privacy. To achieve better results, we enabled the decentralized authentication of legitimate patient wearable devices to minimize computation cost, authentication time, and communication overheads with the help of an ML technique to predicate and forward the authentication attributes of patient wearable devices to the next concerned trusted authority, when it is shifted from region to another region. Simulation upshots of the ML scheme exhibited extraordinary security features with the cost-effective validation of legal patient wearable devices accompanied by worthwhile communication functionalities compared with previous work. However, the application of IoT-based medical devices and managing such a broad, sophisticated medical IoT system on standard Single Cloud platforms (CP) would be extremely tough. We propose a scalable FC with a blockchain-based architecture for a 5G-enabled IoMT platform. To work on an FC architecture with flowing effects, low overheads, and secure storage (SS), this research proposes a secured blockchain-based fogBMIoMT communication mechanism.

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.

According to the security breach level index, millions of records are stolen worldwide on every single day. Personal health records are the most targeted records on the internet, and they are considered sensitive, and valuable. Security and privacy are the most important parameters of cryptography and encryption. They reduce the availability of data on patients and healthcare to the appropriate personnel and ultimately lead to a barrier in the transfer of healthcare into a digital health system. Using a permission blockchain to share healthcare data can reduce security and privacy issues. According to the literature, most healthcare systems rely on a centralized system, which is more prone to security vulnerabilities. The existing blockchain-based healthcare schemes provide only a data-sharing framework, but they lack security and privacy. To cope with these kinds of security issues, we have designed a novel security algorithm that provides security as well as privacy with much better efficiency and a lower cost. Hence, in this research, we have proposed a patient healthcare framework that provides greater security, reliability, and authentication compared to existing blockchain-based access control.

Blockchain is a promising technology in the context of digital healthcare systems, but there are issues related to the control of accessing the electronic health records. In this paper, we propose a novel framework based on blockchain and multiple certificate authority that implement smart contracts and access health records securely. Our proposed solution provides the facilities of flexible policies to update a record or invoke the policy such that a patient has complete authority. A novel approach towards multiple certificate’s authority (CA) is introduced in the design through our proposed framework. Our proposed policies and methods overcome the shortcoming and security breaches faced by single certificate authority. Our proposed scheme provides a flexible access control mechanism for securing electronic health records as compared to the existing benchmark models. Moreover, our proposed method provides a re-enrolment facility in the case of a user lost enrolment.