Ensuring Data Privacy and Security in Smart Healthcare: A Fuzzy Logic Approach

The use of adaptable logic-based frameworks has greatly improved data privacy and security in healthcare places, especially as more and more people depend on IoT and networked technologies. This framework can handle the complexities of cyber security in healthcare by giving people the ability to make decisions that are flexible and smart. The traditional binary logic systems work well in simple situations but they do not work well with healthcare data because it is often unclear and uncertain. The latest logical systems offer a solution by transforming definitive inputs into varying degrees of fact thereby enabling more precise security measures that can adjust to evolving threats. The basic ideas behind fuzzification, rule-based inference and defuzzification help explain how these processes make continual and flexible security solutions possible. In the future, medical information technology and the Internet of Things will need to generate and transmit a lot of private data. These versatile frameworks make it easier to find vulnerabilities and determine vulnerabilities more quickly. Using this approach strengthens security policies and makes them better able to deal with a variety of safety issues such as data breaches and unauthorized access. It is very important for keeping patients trust and privacy. The safety measures make healthcare safer by making it easier to make smart security choices and stay up to date on emerging cyber risks. The significance of integrating intelligent security measures with ethical data governance to safeguard sensitive medical information while ensuring system design remains responsible and ethical.