Software Defined Range-Proof Authentication Mechanism for Untraceable Digital ID

Abstract

The Internet of Things (IoT) is extensively applied across various industrial domains, such as smart homes, factories, and intelligent transportation, becoming integral to daily life. Establishing robust policies for managing and governing IoT devices is imperative. Secure authentication for IoT devices in resource-constrained environments remains challenging due to the limitations of conventional complex protocols. Prior methodologies enhanced mutual authentication through key exchange protocols or complex operations, which are impractical for lightweight devices. To address this, our study introduces the privacy-preserving software-defined range proof (SDRP) model, which achieves secure authentication with low complexity. SDRP minimizes the overhead of confidentiality and authentication processes by utilizing range proof to verify whether the attribute information of a user falls within a specific range. Since authentication is performed using a digital ID sequence generated from indirect personal data, it can avoid the disclosure of actual individual attributes. Experimental results demonstrate that SDRP significantly improves security efficiency, increasing it by an average of 93.02% compared to conventional methods. It mitigates the trade-off between security and efficiency by reducing leakage risk by an av