Persuasive Factors and Weakness for Security Vulnerabilities in BIG IOT Data in Healthcare Solution

Abstract

In the present scenario, public health is a global challenge. In view of COVID-19 pandemic,interventions of emerging technologies hasbeen highly increased and postpandemica big technological shift is expected for providing information and communication Technology-enabled solutions to healthcare as well a meeting other social challenges. Internet of Things or IoT and Big data are the technologies prominently being used in healthcare applications. In smart city visualization to provide ubiquitous computing environment, urge of smart, small but powerful sensor devices or IoT technology-enabled healthcare solutions deployments done over open networked infrastructure and underlying architecture. Such highly dynamic and heterogeneous environment with rapid digital transformation enforcing trusted security resource-restrictions and performance implication. In this paper, firstly, we explore the existing security, privacy and authentication weakness in reference to IoT or IoMT and big data enabled healthcare applications. Secondly, scaling the low to high security risks done based on the major weaknesses. In this work primarily we focus on most challenging attacks like Denial of Services (DoS), Man in the middle and dynamic intrusions. In winding-up machine learning based intelligent adaptive approach proposed for underlying deficiencies and insufficiencies in IoT enabled Healthcare application security. The key driving forces for the imprecision of trust and security with emerging Big IoT also presented as future scope.