Advancing Security with Digital Twins: A Comprehensive Survey

2025-05-22

AI Summary

Electronic supply chains face multifaceted security threats—including counterfeiting, tampering, piracy, data leakage, and side-channel/fault-injection attacks—exacerbated by increasing product complexity and inherent vulnerabilities; existing defenses suffer from poor scalability and inadequate resilience against emerging attacks. This paper systematically surveys digital twin (DT) applications for electronic supply chain security across cyber-physical systems, IoT, and cryptographic hardware. We propose the first unified taxonomy for DT-based security applications; introduce a large language model (LLM)-enhanced security analysis paradigm; and integrate DT modeling, provenance tracking, anomaly detection, side-channel analysis, fault simulation, and LLM orchestration into the first end-to-end security benchmark. We identify six cross-cutting challenges and provide actionable technical pathways, establishing a methodological foundation for industrial-scale trustworthy hardware verification.

Technology Category

• Application Domains: Security
• Machine Learning: Hardware-aware ML
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust

Application Category

• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health

Abstract

The proliferation of electronic devices has greatly transformed every aspect of human life, such as communication, healthcare, transportation, and energy. Unfortunately, the global electronics supply chain is vulnerable to various attacks, including piracy of intellectual properties, tampering, counterfeiting, information leakage, side-channel, and fault injection attacks, due to the complex nature of electronic products and vulnerabilities present in them. Although numerous solutions have been proposed to address these threats, significant gaps remain, particularly in providing scalable and comprehensive protection against emerging attacks. Digital twin, a dynamic virtual replica of a physical system, has emerged as a promising solution to address these issues by providing backward traceability, end-to-end visibility, and continuous verification of component integrity and behavior. In this paper, we present a comprehensive survey of the application of digital twins based on their functional role and application domains. We comprehensively present recent digital twin-based security implementations, including their role in cyber-physical systems, Internet of Things, and cryptographic systems, detection of counterfeit electronics, intrusion detection, fault injection, and side-channel leakage. To the best of our knowledge, it is the first study to consolidate these security use cases into a unified reference. The paper also explores the integration of large language models with digital twins for enhanced security and discusses current challenges, solutions, and future research directions.

Problem

• Addressing vulnerabilities in global electronics supply chain against various attacks
• Exploring digital twins for scalable security in cyber-physical and IoT systems
• Integrating large language models with digital twins to enhance security

Innovation

• Digital twins for electronic security traceability
• Integration with cyber-physical and IoT systems
• Large language models enhance digital twin security