Internet of Things (IoT) is the paramount virtual network that enables remote users to access connected multimedia devices. It has dragged the attention of the community because it encompasses real-world scenarios with implicit environs. Despite several beneficial aspects, IoT is surrounded by provocations for successful implementation, as data travels in different layers. One of the critical challenges is the security of the data in these layers. Researchers conducted numerous studies focusing on the level of security at a single technique, creating loopholes to address the entire scenario of securing an IoT network. This study aims to comprehensively review current security issues, wireless communication techniques, and technologies for securing IoT. This work’s utmost significance is addressing all the security perspectives at a glance. For this purpose, research contributions from the previous years are investigated for better understanding. Some countermeasures and snags from security perspectives have also been analyzed in detail concerning the current industry trends. Blockchain, machine learning, fog, and edge computing are possible solutions to secure IoT. After studying these techniques and their immunity to attacks, machine learning can become a hope if incorporated with end-to-end security. This comprehensive review will provide adequate understanding and knowledge in defining security lines of action for the successful implementation of IoT.

In this study, we introduce a new modification of fractional reduced differential transform method (m-FRDTM) to find exact and approximate solutions for nonhomogeneous linear multiterm time-fractional diffusion equations (MT-TFDEs) of constant coefficients in a bounded domain with suitable initial conditions. Different applications in two and three fractional order terms are given to illustrate our new modification. The approximate solutions are given in the form of series solutions. The results show that the m-FRDTM for MT-TFDEs is a powerful method and can be generalized to other types of multiterm time-fractional equations.

This study deals with the application of new rational bi-cubic Ball function with six parameters in image interpolation, especially for the grayscale image. These six free parameters can be modified to get better and quality image resolution, and refine the shape of the interpolating surface. This bivariate rational Ball function has been extended from univariate cases by using a tensor product approach. The proposed scheme is tested for image upscaling with factors of two and four through an efficient algorithm. The effectiveness of the proposed scheme is measured by using an image quality assessment (IQA), such as peak-signal-to-noise-ratio (PSNR), root mean square error (RMSE) or feature similarity (FSIM) index. Numerical and graphical results with comparisons against some existing scheme are presented by using MATLAB. The proposed scheme resulted in higher PSNR and FSIM, and smaller RMSE. Thus, the new rational bi-cubic Ball with six parameters is better than the existing scheme via an efficient algorithm.

In this work, the effects of plasma parameters on overtaking collisions of ion acoustic multi-shocks are studied in an unmagnetized collisionless plasma with positive and negative ions, and ($\alpha ,q$)-distributed electrons. To investigate such phenomena, the reductive perturbation technique is implemented to derive the Burgers equation. The N-shock wave solution is determined for this equation by directly implementing the exponential function. The result reveals that both the amplitudes and thicknesses of overtaking collisions of N-shock wave compressive and rarefactive electrostatic potential are significantly modified with the influences of viscosity coefficients of positive and negative ions. In addition, the density ratios also play an essential role to the formation of overtaking collisions of N-shocks. It is observed from all theoretical and parametric investigations that the outcomes may be very useful in understanding the dynamical behavior of overtaking collisions of multi-shocks in various environments, especially the D- and F-regions of the Earth’s ionosphere and the future experimental investigations in Q-machine laboratory plasmas.

In this paper, we applied a fractional multi-step differential transformed method, which is a generalization of the multi-step differential transformed method, to find approximate solutions to one of the most important epidemiology and mathematical ecology, fractional stochastic SIS epidemic model with imperfect vaccination, subject to appropriate initial conditions. The fractional derivatives are described in the Caputo sense. Numerical results coupled with graphical representations indicate that the proposed method is robust and precise which can give new interpretations for various types of dynamical systems.

In selecting credit recipients, it is necessary to have a recipient selection system that can overcome the problem of bad credit that often occurs (loans that are not repaid by the debtor). Based on this problem, a decision support system is needed that helps identify the wrong recipient. The method used in this study is the Moora method and the Moosra method, namely the method for determining priorities. A decision support system is a computer-based system consisting of interacting components: a language system component, a knowledge system component, and a problem-handling system component, and uses data and decision-making models to create semi-structured problems. It solves structured problems and semi-structured problems. and assist in decision making. Structured and unstructured problems, this system helps you get information about your customers, the results are more accurate and on target