Pros & Cons of Machine learning and Security Methods

Abstract

In todays world information systems and computerization of business processes by organizations have led to a faster, secure, easier and more accurate data analysis and accuracy. The machine learning techniques have been used increasingly in the analysis of data in various fields from medicine to organization, education and energy applications. Machine learning techniques make it possible to deduct meaningful further information from those data processed by using Different Method. Such meaningful and significant information helps organizations to establish their future policies and able to provide security. This study applies classification machine learning techniques to Process the data also survey of active learning regarding selection methods, query strategies, applications and security. For Security we are using BlockChain Technology.

Blockchain technology is rapidly gaining traction in healthcare industry as one of the most exciting technological developments. In particular, blockchain technology presents numerous opportunities for healthcare industry such as reduced transaction costs, increased transparency for regulatory reporting, efficient healthcare data management and healthcare records universality as well as able to access data from any location. In the context of smart health, blockchain may provide distinct benefits, particularly from a context-aware perspective where efficient and personalized solutions may be provided to citizens and the society in general. In this paper, we are going to discuss relationship between Machine learning and blockchain related to smart health care system. In addition, we discuss several challenges for actually implementing machine learning using blockchain based secure applications in the healthcare industry along with several opportunities for future research directions.