Search

Internet of Things (IoT) deployed healthcare systems to provide ubiquitous services and assistance for the end-users/patients through their handheld devices/user equipment. The processing of sensitive medical information involves the transfer of effective and timely healthcare services without taking rest. In this article, adaptable service compliance (BASC) is implemented for blockchain-reliant purposes to prevent non-dormant healthcare services. The approach proposed is reliable in overcoming dormancy problems when it comes to accessing and providing end-users with health information. This proposed compliance exploits the type of user assistance requirement in the fore-hand. A distributed ledger does not require a central authority to monitor manipulation, and allows a de-centralized dataset to function safely. Based on the requirement, the distributed ledger accessible at ease is selected, and the information is shared with the end-user. In this method, the compliance is valid until the user's requirement is fulfilled by validating the integrity of the transmitted data. For identifying the accessibility of the available ledger, the backpropagation learning method is used to pass the backward pass to correct the weight vector input variables. The output with learning consists of the verification of affordability, and the background verification verifies the data integrity. The truthfulness inability triggers a fresh outlook for information sharing that is visible from the succeeding ledger. This helps to prevent healthcare services failure, postponements in service, and improve the aid's honesty. In addition, improved network access is achieved at various intervals. [ABSTRACT FROM AUTHOR]

Blockchain technology can solve current interoperability challenges in health information systems and provide the technical standard which ensures a secure sharing of electronic health data between individuals, healthcare providers, medical care institutions, and medical experts. In healthcare management, IoMT devices can deliver real-time sensory data from patients to be analyzed and processed. In IoMT devices within a range of product areas, the confidentiality of patients' health data transmission and privacy is still a big problem. In this paper, the Multi-Modal Secure Data Dissemination Framework (MMSDDF) has been proposed based on blockchain in IoMT for secure patient data access and control. To meet the optimized security and privacy requirements of healthcare data management in IoMT devices, the proposed framework is effectively employed. Blockchain's key has been used to a healthcare application network where the patient's health data can create warnings that are significant to authenticated healthcare providers securely. The simulation outcomes show that the suggested MMSDDF method achieves a high accuracy ratio of 95.8%, a prediction ratio of 92.3%, less delay of 0.48 s, latency range of 0.5, and response time of 1.5% to other existing methods. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is made up of intelligent devices that interact with each other. It allows information to be gathered and shared by these devices. In addition, IoT now has a wide range of life applications such as business, logistics, health monitoring, smart ecosystem, and information concerning individuals, social and private environments. Security-related issues involved in such a communication network are drastically increasing day by day. Therefore, existing authentication and authorization concepts must grow along with technological evolution. This paper presents an artificial intelligence (AI)-assisted Bio-inspired algorithm for secure IoT communication networks (AI-BIAS) to improve future communication. The proposed framework is categorized into two sections: First, the Bio-inspired algorithm-assisted blockchain technology for authentication and authorization in the IoT communication network is presented. Further, the Artificial Intelligence algorithm monitors the proposed IoT communication network. The experimental results show that the proposed model enhances the accuracy ratio of 98.3%, average latency of 26 ms, average cost of 25.7%, authentication time 0.04 ms, multistep prediction's MAPE, and RMSE values are 0.7645 and 0.9878 when compared to other popular methods. [ABSTRACT FROM AUTHOR]

The development of the Internet of Things (IoT) widened its definition to incorporate aquatic conditions. The submarine sensor structures and intelligent underwater linked devices have been built into the IoT environment as the Internet of Underwater Things. Energy-sensitive and accurate data collection is carried out using extremely secure communications in underwater sensor networks that face major drawbacks like timing and place-dependent connectivity. Therefore in this paper, Optimized energy planning based intelligent data analytics has been proposed to offer a programming system for distributing intelligent data analytics underwater with high energy efficiency. IDA implements two stages: the first stage is to overcome a drawback caused by secret and expose terminals by a possibility-based disputing method. The second stage investigates the possibilities for slight specificity recovery by adding a space focused on transmitter and receiver. OEP is used to capture data through an activity that uses intelligent data focused on self-learning to identify highly secure and effective route directions across communication gaps in a sensor network. By balancing data traffic loading in a vast network, the OEP transport system minimizes greater energy usage and delay issues. In a controversial approach, IDA resolves a limitation of confidentiality and reveals terminals based on choice. OEP collects data via smart self-learning information to track safety and productive paths through connectivity holes in a sensor network. The experimental findings illustrate the improved results have been built in terms of the high packet distribution rate of 97.11% and low latency, and less energy consumption. [ABSTRACT FROM AUTHOR]

Broadband Wireless Networks is growing rapidly due to the increased number of mobile users. The greatest challenge is to achieve maximum throughput with minimal or no interference while performing concurrent transmission. To reduce the interference problem, this paper proposes a cooperative scheduling and channel assignment algorithm for multi-channel wireless mesh networks. In scheduling algorithm, to avoid the primary interference, the proper time slot is assigned through centralized scheduling for the packet and link in a network. The objective of using the scheduling algorithm is to reduce the transmission delay for uplink/downlink networks. Channel assignment algorithm helps to avoid secondary interference and to perform concurrent transmission with an optimal number of channels. In scheduling, the priority of packets contributes to preventing the accumulation of packets and transmission delay in a multi-hop network. Simulation analysis shows that our channel assignment algorithm avoids both interferences with an optimal number of channels. [ABSTRACT FROM AUTHOR]

Broadband wireless networks namely wireless interoperability for microwave access and long term evolution utilizes the EAP and EPS mechanisms for authentication. However, these mechanisms incur considerable delay during handoffs. This delay during handoffs results in service disruption which becomes a severe bottleneck. To overcome this delay, our article proposes (UPP-KC) a key caching mechanism based on user path prediction. If the user follows the predicted path, he/she bypasses the normal authentication mechanism and obtains the necessary authentication keys directly. Through analytical and simulation modeling, we have proved that our mechanism effectively decreases the handoff delay, thereby achieving fast authentication without compromising on the security standards. [ABSTRACT FROM AUTHOR]