Evaluating Security of Big Data Through Fuzzy Based Decision-Making Technique

Abstract

In recent years, it has been observed that the disclosure of information increases the risk of terrorism. Without restricting the accessibility of information, providing security is difficult. So, there is a demand for time to fill the gap between security and accessibility of information. In fact, security tools should be usable for improving the security as well as the accessibility of information. Though security and accessibility are not directly influenced, some of their factors are indirectly influenced by each other. Attributes play an important role in bridging the gap between security and accessibility. In this paper, we identify the key attributes of accessibility and security that impact directly and indirectly on each other, such as confidentiality, integrity, availability, and severity. The significance of every attribute on the basis of obtained weight is important for its effect on security during the big data security life cycle process. To calculate the proposed work, researchers utilised the Fuzzy Analytic Hierarchy Process (Fuzzy AHP). The findings show that the Fuzzy AHP is a very accurate mechanism for determining the best security solution in a real-time healthcare context. The study also looks at the rapidly evolving security technologies in healthcare that could help improve healthcare services and the future prospects in this area.