No abstract

Blockchain and IoT are being deployed at a large scale in various fields including healthcare for applications such as secure storage, transactions, and process automation. IoT devices are resource-constrained, have no capability of security and self-protection, and can easily be hacked or compromised. Furthermore, Blockchain is an emerging technology with immutability features which provide secure management, authentication, and guaranteed access control to IoT devices. IoT is a cloud-based internet service in which processing and collection of user’s data are accomplished remotely. Smart healthcare also requires the facility to provide the diagnosis of patients located remotely. The smart health framework faces critical issues such as data security, costs, memory, scalability, trust, and transparency between different platforms. Therefore, it is important to handle data integrity and privacy as the user’s authenticity is in question due to an open internet environment. Several techniques are available that primarily focus on resolving security issues i.e., forgery, timing, denial of service and stolen smartcard attacks, etc. Blockchain technology follows the rules of absolute privacy to identify the users associated with transactions. The motivation behind the use of Blockchain in health informatics is the removal of the centralized third party, immutability, improved data sharing, enhanced security, and reduced overhead costs in distributed applications. Healthcare informatics has some specific requirements associated with the security and privacy along with the additional legal requirements. This paper presents a novel authentication and authorization framework for Blockchain-enabled IoT networks using a probabilistic model. The proposed framework makes use of random numbers in the authentication process which is further connected through joint conditional probability. Hence, it establishes a secure connection among IoT devices for further data acquisition. The proposed model is validated and evaluated through extensive simulations using the AVISPA tool and the Cooja simulator, respectively. Experimental results analyses show that the proposed framework provides robust mutual authenticity, enhanced access control, and lowers both the communication and computational overhead cost as compared to others.

The fractional order Susceptible-Infected-Recovered (SIR) epidemic model of childhood disease is considered. Laplace-Adomian Decomposition Method is used to compute an approximate solution of the system of nonlinear fractional differential equations. We obtain the solutions of fractional differential equations in the form of infinite series. The series solution of the proposed model converges rapidly to its exact value. The obtained results are compared with the classical case.

Graphical abstract

Nature-inspired optimization techniques are useful tools in electrical engineering problems to minimize or maximize an objective function. In this paper, we use the firefly algorithm to improve the optimal solution for the problem of directional overcurrent relays (DOCRs). It is a complex and highly nonlinear constrained optimization problem. In this problem, we have two types of design variables, which are variables for plug settings (PSs) and the time dial settings (TDSs) for each relay in the circuit. The objective function is to minimize the total operating time of all the basic relays to avoid unnecessary delays. We have considered four models in this paper which are IEEE (3-bus, 4-bus, 6-bus, and 8-bus) models. From the numerical results, it is obvious that the firefly algorithm with certain parameter settings performs better than the other state-of-the-art algorithms.