A Privacy-Aware Tracking and Tracing System

Abstract

The ability to track and trace assets in the supply chain is becoming increasingly important. In addition to asset tracking, the technologies used provide new opportunities for collecting and analyzing employee position and biometric data. As a result, these technologies can be used to monitor performance or track worker behavior, resulting in additional risks and stress for employees. Furthermore, contact tracing systems used to contain the COVID-19 outbreak have made positive patients' privacy public, resulting in violations of users' rights and even endangering their lives. To resolve this situation, a verifiable attributebased encryption (ABE) scheme based on homomorphic encryption and zero-knowledge identification (ZKI) is proposed, with ZKI providing anonymity for data owners to resist tracking attacks and homomorphic encryption used to solve the problem of privacy leakage from location inquiries returned from a semi-honest server. Finally, theoretical security analysis and formal security verification show that our scheme is secure against the chosen plaintext attack (CPA) and other attacks. Besides that, our novel scheme is efficient enough in terms of user-side computation overhead for practical applications.