The importance of image security in the field of medical imaging is challenging. Several research works have been conducted to secure medical healthcare images. Encryption, not risking loss of data, is the right solution for image confidentiality. Due to data size limitations, redundancy, and capacity, traditional encryption techniques cannot be applied directly to e-health data, especially when patient data are transferred over the open channels. Therefore, patients may lose the privacy of data contents since images are different from the text because of their two particular factors of loss of data and confidentiality.Researchers have identified such security threats and have proposed several image encryption techniques to mitigate the security problem. However, the study has found that the existing proposed techniques still face application-specific several security problems. Therefore, this paper presents an efficient, lightweight encryption algorithm to develop a secure image encryption technique for the healthcare industry. The proposed lightweight encryption technique employs two permutation techniques to secure medical images. The proposed technique is analyzed, evaluated, and then compared to conventionally encrypted ones in security and execution time. Numerous test images have been used to determine the performance of the proposed algorithm. Several experiments show that the proposed algorithm for image cryptosystems provides better efficiency than conventional techniques.INDEX TERMS Internet of Medical Things, medical image encryption, lightweight encryption.

This paper introduces an effective Selective Harmonic Elimination (SHE) modulation technique in a five, seven, and nine-level cascaded H-bridge (CHB) multilevel inverter (MLI). Minimization of the harmonics and device counts is the basis for the ongoing research in the area of MLI. Reduced harmonics and hence the lower Total Harmonic Distortion (THD), improve the output power quality. SHE is a low-frequency modulation scheme to achieve this goal. SHE techniques are used to eliminate the distinct lower-order harmonics by determining the optimum switching angles. These angles are evaluated by solving the non-linear transcendental equations using any optimization technique. For this purpose, the Crystal Structure Algorithm (CryStAl) has been used in this paper. It is a metaheuristic, nature-inspired, and highly efficient optimization technique. CryStAl is a simple and parameter-free algorithm that doesn’t require the determination of any internal parameter during the optimization process. It is based on the concept of crystal structure formation by joining the basis and lattice point. This natural occurrence can be realized in crystalline minerals in their symmetrically organized components: ions, atoms, and molecules. The concept has been utilized to solve non-linear transcendental equations. SIMULINK/MATLAB environment has been used for the simulation. The simulation result shows that the crystal structure algorithm is very effective and excels the other metaheuristic algorithm. Hardware results validate the performance.

Automation is being fueled by a multifaceted approach to technological advancements, which includes advances in artificial intelligence, robotics, sensors, and cloud computing. The use of automated, as opposed to conventional, systems, has become more popular in recent years. Modern agricultural technology has played an important role in the development of Saudi Arabia in addition to upgrading infrastructure and plans. Agriculture in Saudi Arabia is dependent upon wells, which are insufficient in terms of water supplies. Thus, irrigation is used for agricultural fields, depending on the soil type, and water is provided to the plants. Two essential elements are necessary for farming, the first is the ability to determine the soil’s fertility, and the second is the use of different technologies to reduce the dependence of water on electrical power and on/off schedules. The purpose of this study is to propose a system in which moisture sensors are placed under trees or plants. The gateway unit transmits sensor information to the controller, which then turns on the pump and recycles the water flow. A farmland’s water pump can be remotely controlled and parameters such as moisture and flow rate can be monitored using an HTTP dashboard. In order to evaluate the applicability of IOT-based automatic wastewater irrigation systems, a pilot test was conducted using the developed framework. Theoretically, such a system could be expanded by including any pre-defined selection parameters.

The Internet of Things (IoT) supports human endeavors by creating smart environments. Although the IoT has enabled many human comforts and enhanced business opportunities, it has also opened the door to intruders or attackers who can exploit the technology, either through attacks or by eluding it. Hence, security and privacy are the key concerns for IoT networks. To date, numerous intrusion detection systems (IDS) have been designed for IoT networks, using various optimization techniques. However, with the increase in data dimensionality, the search space has expanded dramatically, thereby posing significant challenges to optimization methods, including particle swarm optimization (PSO). In light of these challenges, this paper proposes a method called improved dynamic sticky binary particle swarm optimization (IDSBPSO) for feature selection, introducing a dynamic search space reduction strategy and a number of dynamic parameters to enhance the searchability of sticky binary particle swarm optimization (SBPSO). Through this approach, an IDS was designed to detect malicious data traffic in IoT networks. The proposed model was evaluated using two IoT network datasets: IoTID20 and UNSW-NB15. It was observed that in most cases, IDSBPSO obtained either higher or similar accuracy even with less number of features. Moreover, IDSBPSO substantially reduced computational cost and prediction time, compared with conventional PSO-based feature selection methods.

Internet of Things (IoT) as refers to a network of devices that have the ability to connect, collect and exchange data with other devices over the Internet. IoT is a revolutionary technology that have tremendous applications in numerous fields of engineering and sciences such as logistics, healthcare, traffic, oil and gas industries and agriculture. In agriculture field, the farmer still used conventional agriculture methods resulting in low crop and fruit yields. The integration of IoT in conventional agriculture methods has led to significant developments in agriculture field. Different sensors and IoT devices are providing services to automate agriculture precision and to monitor crop conditions. These IoT devices are deployed in agriculture environment to increase yields production by making smart farming decisions and to collect data regarding crops temperature, humidity and irrigation systems. However, the integration of IoT and smart communication technologies in agriculture environment introduces cyber security attacks and vulnerabilities. Such cyber attacks have the capability to adversely affect the countries’ economies that are heavily reliant on agriculture. On the other hand, these IoT devices are resource constrained having limited memory and power capabilities and cannot be secured using conventional cyber security protocols. Therefore, designing robust and efficient secure framework for smart agriculture are required. In this paper, a Cyber Secured Framework for Smart Agriculture (CSFSA) is proposed. The proposed CSFSA presents a robust and tamper resistant authentication scheme for IoT devices using Constrained Application Protocol (CoAP) to ensure the data integrity and authenticity. The proposed CSFSA is demonstrated in Contiki NG simulation tool and greatly reduces packet size, communication overhead and power consumption. The performance of proposed CSFSA is computationally efficient and is resilient against various cyber security attacks i.e., replay attacks, Denial of Service (DoS) attacks, resource exhaustion.