A Quantitative Approach of Purposive Sampling Techniques for Security and Privacy Issues in IoT Healthcare Applications

Abstract

The internet of things (IoT) offers several benefits to the healthcare industry, including the ability to actively monitor patients and use data for analytics. For medical device integration, the focus has moved to the consumer end of the IoT, that captures data on patient vital signs. Unfortunately, when healthcare centers link these devices to the internet, they typically overlook security concerns. Short-term monitoring and emergency alerting of healthcare signals are becoming increasingly accessible thanks to the Internet of Things (IoT). Data secrecy is critical hence, encryption is required out of real concern. In this book chapter, we explore the privacy and security issues of Internet of Things (IoT) healthcare applications for special needs users. IoT enables health-related enterprises to lift necessary data from diverse sources in real-time and this helps in accurate decision-making to reducing data vulnerability and therefore creating opportunities for secure patient data, particularly for special needs patients.