Ethical Adaptive Security Algorithm for Cross-Platform IoT-Enabled Metaverse Applications

The prompt expansion of the Metaverse presents challenges for secure and ethical user interactions. Existing security frameworks often lack integration of ethical considerations such as user consent and regulatory compliance. This study develops an Ethical Adaptive Security Algorithm (EASA) that embeds ethical principles into Metaverse security mechanisms. EASA incorporates a dynamic User Consent Management System, modeled as a time-dependent consent function, that gives users control over their data. Integrate ethical parameters into security actions using compliance and transparency functions. The framework employs mathematical constructs, including consent differential equations and optimization problems, to balance user satisfaction and ethical considerations. EASA was evaluated through simulations in MATLAB R2021b and results showed that EASA achieved a detection accuracy of 98.5% in low-traffic scenarios, outperforming existing models by at least 6.2%.