Privacy-preserving Robotic-based Multi-factor Authentication Scheme for Secure Automated Delivery System

• URL: http://arxiv.org/abs/2411.18027v1
• Date: Wed, 27 Nov 2024 03:48:00 GMT
• Title: Privacy-preserving Robotic-based Multi-factor Authentication Scheme for Secure Automated Delivery System
• Authors: Yang Yang, Aryan Mohammadi Pasikhani, Prosanta Gope, Biplab Sikdar,
• Abstract summary: Package delivery is a critical aspect of various industries, but it often incurs high financial costs and inefficiencies when relying solely on human resources. Last-mile transport problem contributes significantly to the expenditure of human resources in major companies. Robot-based delivery systems have emerged as a potential solution for last-mile delivery to address this challenge.
• Score: 17.475266664325904
• License:
• Abstract: Package delivery is a critical aspect of various industries, but it often incurs high financial costs and inefficiencies when relying solely on human resources. The last-mile transport problem, in particular, contributes significantly to the expenditure of human resources in major companies. Robot-based delivery systems have emerged as a potential solution for last-mile delivery to address this challenge. However, robotic delivery systems still face security and privacy issues, like impersonation, replay, man-in-the-middle attacks (MITM), unlinkability, and identity theft. In this context, we propose a privacy-preserving multi-factor authentication scheme specifically designed for robot delivery systems. Additionally, AI-assisted robotic delivery systems are susceptible to machine learning-based attacks (e.g. FGSM, PGD, etc.). We introduce the \emph{first} transformer-based audio-visual fusion defender to tackle this issue, which effectively provides resilience against adversarial samples. Furthermore, we provide a rigorous formal analysis of the proposed protocol and also analyse the protocol security using a popular symbolic proof tool called ProVerif and Scyther. Finally, we present a real-world implementation of the proposed robotic system with the computation cost and energy consumption analysis. Code and pre-trained models are available at: https://drive.google.com/drive/folders/18B2YbxtV0Pyj5RSFX-ZzCGtFOyorBHil

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