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The new generation of the wireless body area networks (WBAN) for internet of things (IoT) is emerging in a fast-paced. Today patients can be tested using remote clinical nanosensors. WBAN involves interconnected small sensors for the collection of ongoing medical data and transmitted through the networks for further processing. However, the protection of healthcare data is very important and difficult because of the various active and passive numbers of attacks. Although there exists several literature on data security techniques such as digital signatures, Elliptic curve cryptography, and Advanced Encryption Standards (AES) they contain stumbling blocks for the security methodologies. Thus, in this paper, a novel data protection genetic-based encryption scheme is proposed for higher performance.INDEX TERMS WBAN security, genetic based algorithm, cryptography, healthcare data security, man-inmiddle attack, internet of nano things

COVID-19 is a novel coronavirus disease that has been declared as a global pandemic in 2019. It affects the whole world through personto-person communication. This virus spreads by the droplets of coughs and sneezing, which are quickly falling over the surface. Therefore, anyone can get easily affected by breathing in the vicinity of the COVID-19 patient. Currently, vaccine for the disease is under clinical investigation in different pharmaceutical companies. Until now, multiple medical companies have delivered health monitoring kits. However, a wireless body area network (WBAN) is a healthcare system that consists of nano sensors used to detect the real-time health condition of the patient. The proposed approach delineates is to fill a gap between recent technology trends and healthcare structure. If COVID-19 affected patient is monitored through WBAN sensors and network, a physician or a doctor can guide the patient at the right time with the correct possible decision. This scenario helps the community to maintain social distancing and avoids an unpleasant environment for hospitalized patients Herein, a Monte Carlo algorithm guided protocol is developed to probe a secured cipher output. Security cipher helps to avoid wireless network issues like packet loss, network attacks, network interference, and routing problems. Monte Carlo based covid-19 detection technique gives 90% better results in terms of time complexity, performance, and efficiency. Results indicate that Monte Carlo based covid-19 detection technique with edge computing idea is robust in terms of time complexity, performance, and efficiency and thus, is advocated as a significant application for lessening hospital expenses.

Programmable Object Interfaces are increasingly intriguing researchers because of their broader applications, especially in the medical field. In a Wireless Body Area Network (WBAN), for example, patients’ health can be monitored using clinical nano sensors. Exchanging such sensitive data requires a high level of security and protection against attacks. To that end, the literature is rich with security schemes that include the advanced encryption standard, secure hashing algorithm, and digital signatures that aim to secure the data exchange. However, such schemes elevate the time complexity, rendering the data transmission slower. Cognitive radio technology with a medical body area network system involves communication links between WBAN gateways, server and nano sensors, which renders the entire system vulnerable to security attacks. In this paper, a novel DNA-based encryption technique is proposed to secure medical data sharing between sensing devices and central repositories. It has less computational time throughout authentication, encryption, and decryption. Our analysis of experimental attack scenarios shows that our technique is better than its counterparts.

The Internet of Things (IoT) uses wireless networks without infrastructure to install a huge number of wireless sensors that track system, physical, and environmental factors. There are a variety of WSN uses, and some well-known application factors include energy consumption and lifespan duration for routing purposes. The sensors have detecting, processing, and communication capabilities. In this paper, an intelligent healthcare system is proposed which consists of nano sensors that collect real-time health status and transfer it to the doctor’s server. Time consumption and various attacks are major concerns, and some existing techniques contain stumbling blocks. Therefore, in this research, a genetic-based encryption method is advocated to protect data transmitted over a wireless channel using sensors to avoid an uncomfortable data transmission environment. An authentication procedure is also proposed for legitimate users to access the data channel. Results show that the proposed algorithm is lightweight and energy efficient, and time consumption is 90% lower with a higher security ratio.