Advancing Security with Digital Twins: A Comprehensive Survey

• URL: http://arxiv.org/abs/2505.17310v1
• Date: Thu, 22 May 2025 22:01:07 GMT
• Title: Advancing Security with Digital Twins: A Comprehensive Survey
• Authors: Blessing Airehenbuwa, Touseef Hasan, Souvika Sarkar, Ujjwal Guin,
• Abstract summary: Digital twins provide backward traceability, end-to-end visibility, and continuous verification of component integrity and behavior.<n>We present recent digital twin-based security implementations in cyber-physical systems, Internet of Things, cryptographic systems, detection of counterfeit electronics, intrusion detection, fault injection, and side-channel leakage.
• Score: 2.4936576553283287
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

Related papers

• Modern DDoS Threats and Countermeasures: Insights into Emerging Attacks and Detection Strategies [49.57278643040602]
  Distributed Denial of Service (DDoS) attacks persist as significant threats to online services and infrastructure.<n>This paper offers a comprehensive survey of emerging DDoS attacks and detection strategies over the past decade.
  arXiv  Detail & Related papers  (2025-02-27T11:22:25Z)
• Fingerprinting of Machines in Critical Systems for Integrity Monitoring and Verification [0.0]
  It has become increasingly challenging to identify the root causes of security breaches that occur between periodic security assessments.<n>This paper explores the fundamental importance of system fingerprinting as a proactive and effective approach to addressing this issue.
  arXiv  Detail & Related papers  (2024-12-21T12:00:33Z)
• Digital Twin for Evaluating Detective Countermeasures in Smart Grid Cybersecurity [0.0]
  This study delves into the potential of digital twins, replicating a smart grid's cyber-physical laboratory environment.<n>We introduce a flexible, comprehensive digital twin model equipped for hardware-in-the-loop evaluations.
  arXiv  Detail & Related papers  (2024-12-05T08:41:08Z)
• A Survey of Wireless Sensing Security from a Role-Based View: Victim, Weapon, and Shield [19.611803729399092]
  This paper presents the first comprehensive survey of wireless sensing security through a role-based perspective.<n>We propose a novel classification framework that systematically categorizes existing research into three main classes: wireless systems as victims of attacks, wireless signals as weapons for attacks, and wireless signals as shields for security applications.
  arXiv  Detail & Related papers  (2024-12-04T06:34:36Z)
• ACRIC: Securing Legacy Communication Networks via Authenticated Cyclic Redundancy Integrity Check [98.34702864029796]
  Recent security incidents in safety-critical industries exposed how the lack of proper message authentication enables attackers to inject malicious commands or alter system behavior.<n>These shortcomings have prompted new regulations that emphasize the pressing need to strengthen cybersecurity.<n>We introduce ACRIC, a message authentication solution to secure legacy industrial communications.
  arXiv  Detail & Related papers  (2024-11-21T18:26:05Z)
• Principles of Designing Robust Remote Face Anti-Spoofing Systems [60.05766968805833]
  This paper sheds light on the vulnerabilities of state-of-the-art face anti-spoofing methods against digital attacks. It presents a comprehensive taxonomy of common threats encountered in face anti-spoofing systems.
  arXiv  Detail & Related papers  (2024-06-06T02:05:35Z)
• Securing the Digital World: Protecting smart infrastructures and digital industries with Artificial Intelligence (AI)-enabled malware and intrusion detection [0.0]
  cybercrime has emerged as a global threat to governments, businesses, and civil societies. This paper investigates AI-based cyber threat detection to protect our modern digital ecosystems.
  arXiv  Detail & Related papers  (2023-10-15T09:35:56Z)
• Forensic Data Analytics for Anomaly Detection in Evolving Networks [13.845204373507016]
  Many cybercrimes and attacks have been launched in evolving networks to perform malicious activities. This chapter presents a digital analytics framework for network anomaly detection. Experiments on real-world evolving network data show the effectiveness of the proposed forensic data analytics solution.
  arXiv  Detail & Related papers  (2023-08-17T20:09:33Z)
• Graph Mining for Cybersecurity: A Survey [61.505995908021525]
  The explosive growth of cyber attacks nowadays, such as malware, spam, and intrusions, caused severe consequences on society. Traditional Machine Learning (ML) based methods are extensively used in detecting cyber threats, but they hardly model the correlations between real-world cyber entities. With the proliferation of graph mining techniques, many researchers investigated these techniques for capturing correlations between cyber entities and achieving high performance.
  arXiv  Detail & Related papers  (2023-04-02T08:43:03Z)
• Biometrics: Trust, but Verify [49.9641823975828]
  Biometric recognition has exploded into a plethora of different applications around the globe. There are a number of outstanding problems and concerns pertaining to the various sub-modules of biometric recognition systems.
  arXiv  Detail & Related papers  (2021-05-14T03:07:25Z)
• Dos and Don'ts of Machine Learning in Computer Security [74.1816306998445]
  Despite great potential, machine learning in security is prone to subtle pitfalls that undermine its performance. We identify common pitfalls in the design, implementation, and evaluation of learning-based security systems. We propose actionable recommendations to support researchers in avoiding or mitigating the pitfalls where possible.
  arXiv  Detail & Related papers  (2020-10-19T13:09:31Z)
• Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain [58.30296637276011]
  This paper summarizes the latest research on adversarial attacks against security solutions based on machine learning techniques. It is the first to discuss the unique challenges of implementing end-to-end adversarial attacks in the cyber security domain.
  arXiv  Detail & Related papers  (2020-07-05T18:22:40Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.