The Integration of Connectivity and System Integrity Approaches using Machine Learning for Enhancing Network Security

The practise of environment monitoring has substantially advanced because to recent developments in technology for communication, “like the Internet of Things (IoT)”. Technological solutions have the capacity to track, analyse, and understand our surroundings, enabling modernizations that improve the standard of living. Billion intelligent gadgets are connected via the “Internet of Things (IoT)”, so they may easily communicate with each other. It is the computer industry with the quickest rate of growth. On the one hand, Technological solutions are essential for improving a number of practical smart applications that can raise the quality of life. “Machine learning, the Internet of Things”, and other cutting-edge digital technologies enable management to acquire, analyse, interpret, and store huge volumes of data quickly and effectively. Content that may be retrieved later can also be saved using these techniques. This also puts the organization's ability to protect the information and data needed to sufficiently improve network security in grave danger. The purpose of this study is to illustrate how machine learning may be used to integrate connectivity and system integrity techniques for boosting network security. The researchers have critically explained the research topic comprehensively by adopting appropriate research methodology. Furthermore, This study has taken into account secondary and empirical research to gather relevant information related to research topic.