Quantum AI and IoT Cognitive Disease Data Security to Evade Quantum Computing Attacks

Abstract

The aim of the chapter is to provide the enormous profits of the IoT systems (or) devices vulnerable to highly capable intrusions of different attackers. The vital security necessities such as authorization and authentication do not satisfactorily meet the requirements, and prevailing events are not capable of securing the IoT innovative healthcare environment from data gaps of the system security. With the number of IoT application domains growing to incorporate smart homes, mobile healthcare, autonomous intelligent healthcare communication, and smart cities in day-to-day human life, the significance of an attack in the IoT intelligent healthcare networks will become serious. As there are many issues in applying present cryptographic principles to resource-constrained IoT sensor devices, the recommended new security features solutions come with a compromise between security, feasibility, and performance. These research topics focus on evolving lightweight cryptographic results that specifically implement the post-quantum McEliece cryptography algorithm to encrypt the IoT intelligent healthcare device data, which is integrated into the classical blockchain with hashing function SHA-512. The evolving quantum computing integration with AI is together a transformational technology. The AI requires quantum computing power to attain substantial advancement to analyze the enormous data set faster, specifically the mental medical images or patient data.