Neutrosophic Intelligence Approach Safeguarding Patient Data in Blockchain-based Smart Healthcare

Abstract

In the ever-evolving landscape of blockchain-based smart healthcare, ensuring the security and
integrity of patient data stands as an utmost priority. This paper is dedicated to unveiling the pivotal role
of Neutrosophic sets theory within our methodology as we tackle the multifaceted challenges of
safeguarding patient data. Central to our approach is the innovative integration of Neutrosophic sets
theory, a mathematical framework adept at handling the inherent uncertainties and imprecisions often
encountered in healthcare decision-making. Leveraging Neutrosophic sets, we construct a comprehensive
evaluation model that accommodates the complexities of the smart healthcare environment. Our
methodology harnesses Multi-Criteria Decision Making (MCDM) techniques, notably the Technique for
Order Preference by Similarity to Ideal Solution (TOPSIS), to systematically assess and rank service
providers based on their proximity to ideal solutions. The Neutrosophic aspect comes to the forefront as
we apply Neutrosophic sets in representing and managing decision-makers' judgments, which often
exhibit varying degrees of truth, indeterminacy, and falsity. Furthermore, the Ordered Weighted Averaging
(OWA) operator is strategically employed to aggregate these Neutrosophic judgments, accentuating the
role of Neutrosophic sets in our decision fusion process. Our empirical study, firmly rooted in
Neutrosophic sets theory, showcases the efficacy of this innovative model. It offers a structured and robust
framework for healthcare organizations to fortify patient data security in the realm of blockchain-based
smart healthcare systems. This paper advances the understanding of the indispensable role played by
Neutrosophic sets in enhancing data security, thereby facilitating the adoption of blockchain technology
within healthcare, while contributing to the burgeoning field of Neutrosophic Intelligence.