DATAGUARDIAN: EFFICIENT AUTHENTICATION AND PRIVACY PROTECTION IN IOT NETWORKS

Abstract

The rapid proliferation of Internet of Things (IoT) devices has introduced unprecedented opportunities for automation, data collection, and intelligent decisionmaking across various domains. However, these devices are highly susceptible to security threats, unauthorized access, and privacy breaches due to their limited computational resources and often unsecured communication channels. This study presents DataGuardian, an enhanced privacy-preserving framework designed for secure and efficient data authentication in IoT networks. Leveraging lightweight cryptographic algorithms and attribute-based authentication mechanisms, DataGuardian ensures that only authorized entities can access sensitive data while maintaining minimal computational overhead. Experimental evaluations demonstrate that the framework achieves high security, low latency, and efficient resource utilization, making it suitable for largescale IoT deployments. The proposed approach provides a robust solution for enhancing trust, safeguarding privacy, and improving reliability in IoT ecosystems.