Blockchain-based Security Model to Mitigate the Risks of a Database for a Public Organization

Abstract

Effective information management is pivotal for public organizations, particularly in developing regions like Latin America, where cybersecurity capabilities are limited, leaving them vulnerable to increasingly sophisticated cyber threats, resulting in economic losses and reputational damage. This paper aims to design a security model leveraging Blockchain and Machine Learning technologies to mitigate the risks associated with information systems and databases in public organizations. Employing the deductive method and exploratory research, we analyzed scientific articles pertaining to security models and methodologies incorporating Blockchain and Machine Learning, culminating in the proposal of a novel security model tailored to public organizations. Additionally, we introduced a transaction management procedure for evaluating security models for public organization databases. The adoption of a layered model integrating Blockchain and Machine Learning significantly enhances security in public organizations, achieving effectiveness levels ranging from 80% to 98%. Furthermore, the amalgamation of Blockchain, Machine Learning, and artificial intelligence facilitates risk reduction and threat mitigation, thereby bolstering global security.