Abstract
Digital Twin (DT) impacts significantly to both industries and research. It has emerged as a promising technology enabling us to add value to our lives and society. DT enables us to virtualize any physical systems and observe real-time dynamics of their status, processes, and functions by using the data obtained from the physical counterpart. This paper attempts to explore a new direction to enhance cyber resilience in the perspective of cybersecurity and Digital Twins. We enumerate definitions of the Digital Twin concept to introduce readers to this disruptive concept. We then explore the existing literature to develop a holistic analysis of the DT’s integration into cybersecurity. Our research questions develop a novel roadmap for a promising direction of research, which is worth exploring in the future and is validated by an extensive and systematic survey of recent works. Our research has aimed to properly illustrate the current research state in this area and can benefit both community and industry to further the integration of Digital Twins into Cybersecurity.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ahmadi-Assalemi, G., et al.: Digital twins for precision healthcare. In: Jahankhani, H., Kendzierskyj, S., Chelvachandran, N., Ibarra, J. (eds.) Cyber Defence in the Age of AI, Smart Societies and Augmented Humanity. ASTSA, pp. 133–158. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-35746-7_8
Ahmadi-Assalemi, G., Al-Khateeb, H.M., Epiphaniou, G., Cosson, J., Jahankhani, H., Pillai, P.: Federated blockchain-based tracking and liability attribution framework for employees and cyber-physical objects in a smart workplace. In: Proceedings of the 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3), pp. 1–9. IEEE (2019)
Akbarian, F., Fitzgerald, E., Kihl, M.: Intrusion detection in digital twins for industrial control systems. In: Proceedings of the 2020 International Conference on Software, Telecommunications and Computer Networks (SoftCOM), pp. 1–6. IEEE (2020)
Aldwairi, T., Perera, D., Novotny, M.A.: An evaluation of the performance of restricted Boltzmann machines as a model for anomaly network intrusion detection. Comput. Networks 144, 111–119 (2018)
Babu, S.: Detecting anomalies in Users-An UEBA approach. In: Proceedings of the International Conference on Industrial Engineering and Operations Management, pp. 863–876 (2020)
Barricelli, B.R., Casiraghi, E., Fogli, D.: A survey on digital twin: definitions, characteristics, applications, and design implications. IEEE Access 7, 167653–167671 (2019)
Becue, A., et al.: Cyberfactory# 1-securing the industry 4.0 with cyber-ranges and digital twins. In: Proceedings of the 2018 14th IEEE International Workshop on Factory Communication Systems (WFCS), pp. 1–4. IEEE (2018)
Becue, A., Maia, E., Feeken, L., Borchers, P., Praca, I.: A new concept of digital twin supporting optimization and resilience of factories of the future. Appl. Sci. 10(13), 4482 (2020)
Bitton, R., et al.: Deriving a cost-effective digital twin of an ICS to facilitate security evaluation. In: Lopez, J., Zhou, J., Soriano, M. (eds.) ESORICS 2018. LNCS, vol. 11098, pp. 533–554. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-99073-6_26
Bruynseels, K., Santoni de Sio, F., van den Hoven, J.: Digital twins in health care: ethical implications of an emerging engineering paradigm. Front. Genet. 9, 31 (2018)
Buldakova, T., Suyatinov, S.: Hierarchy of human operator models for digital twin. In: Proceedings of the 2019 International Russian Automation Conference (RusAutoCon), pp. 1–5. IEEE (2019)
Caselli, M., Zambon, E., Amann, J., Sommer, R., Kargl, F.: Specification mining for intrusion detection in networked control systems. In: Proceedings of the 25th USENIX Security Symposium (USENIX Security 16), pp. 791–806 (2016)
Cheh, C., Keefe, K., Feddersen, B., Chen, B., Temple, W.G., Sanders, W.H.: Developing models for physical attacks in cyber-physical systems. In: Proceedings of the 2017 Workshop on Cyber-Physical Systems Security and Privacy, pp. 49–55 (2017)
Chen, X., et al.: Android HIV: a study of repackaging malware for evading machine-learning detection. IEEE Trans. Inf. Forensics Secur. 15, 987–1001 (2019)
Coppinger, R.: Design through the looking glass [digital twins of real products]. Eng. Technol. 11(11), 58–60 (2016)
Damjanovic-Behrendt, V.: A digital twin-based privacy enhancement mechanism for the automotive industry. In: 2018 International Conference on Intelligent Systems (IS), pp. 272–279. IEEE (2018)
Dietz, M., Pernul, G.: Unleashing the digital twin’s potential for ICS security. IEEE Secur. Priv. 18(4), 20–27 (2020)
Dietz, M., Putz, B., Pernul, G.: A distributed ledger approach to digital twin secure data sharing. In: Foley, S.N. (ed.) DBSec 2019. LNCS, vol. 11559, pp. 281–300. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22479-0_15
Dietz, M., Vielberth, M., Pernul, G.: Integrating digital twin security simulations in the security operations center. In: Proceedings of the 15th International Conference on Availability, Reliability and Security, pp. 1–9 (2020)
Eckhart, M., Ekelhart, A.: A specification-based state replication approach for digital twins. In: Proceedings of the 2018 Workshop on Cyber-Physical Systems Security and Privacy, pp. 36–47 (2018)
Eckhart, M., Ekelhart, A.: Towards security-aware virtual environments for digital twins. In: Proceedings of the 4th ACM Workshop on Cyber-physical System Security, pp. 61–72 (2018)
Eckhart, M., Ekelhart, A.: Digital twins for cyber-physical systems security: state of the art and outlook. In: Security and Quality in Cyber-Physical Systems Engineering, pp. 383–412. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-25312-7_14
Farsi, M., Daneshkhah, A., Hosseinian-Far, A., Jahankhani, H.: Digital Twin Technologies and Smart Cities. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-18732-3
Graessler, I., Pöhler, A.: Integration of a digital twin as human representation in a scheduling procedure of a cyber-physical production system. In: Proceedings of the 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), pp. 289–293. IEEE (2017)
Grieves, M., Vickers, J.: Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems. In: Kahlen, F.-J., Flumerfelt, S., Alves, A. (eds.) Transdisciplinary Perspectives on Complex Systems, pp. 85–113. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-38756-7_4
Hallaq, B., Nicholson, A., Smith, R., Maglaras, L., Janicke, H., Jones, K.: CYRAN: a hybrid cyber range for testing security on ICS/SCADA systems. In: Cyber Security and Threats: Concepts, Methodologies, Tools, and Applications, pp. 622–637. IGI Global (2018)
Hearn, M., Rix, S.: Cybersecurity considerations for digital twin implementations. IIC J. Innov. 107–113 (2019)
Jones, D., Snider, C., Nassehi, A., Yon, J., Hicks, B.: Characterising the digital twin: a systematic literature review. CIRP J. Manuf. Sci. Technol. 29, 36–52 (2020)
Katzenbeisser, S., Petitcolas, F.: Digital Watermarking. Artech House, London 2 (2000)
Kaur, M.J., Mishra, V.P., Maheshwari, P.: The convergence of digital twin, IoT, and machine learning: transforming data into action. In: Farsi, M., Daneshkhah, A., Hosseinian-Far, A., Jahankhani, H. (eds.) Digital Twin Technologies and Smart Cities. IT, pp. 3–17. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-18732-3_1
Laaki, H., Miche, Y., Tammi, K.: Prototyping a digital twin for real time remote control over mobile networks: application of remote surgery. IEEE Access 7, 20325–20336 (2019)
Liao, H.J., Lin, C.H.R., Lin, Y.C., Tung, K.Y.: Intrusion detection system: a comprehensive review. J. Network Comput. Appl. 36(1), 16–24 (2013)
Lim, K.Y.H., Zheng, P., Chen, C.H.: A state-of-the-art survey of digital twin: techniques, engineering product lifecycle management and business innovation perspectives. J. Intell. Manuf. 31(6), 1–25 (2019)
Liu, L., De Vel, O., Han, Q.L., Zhang, J., Xiang, Y.: Detecting and preventing cyber insider threats: a survey. IEEE Commun. Surv. Tutorials 20(2), 1397–1417 (2018)
Liu, M., Fang, S., Dong, H., Xu, C.: Review of digital twin about concepts, technologies, and industrial applications. J. Manuf. Syst. 58, 346–361 (2020)
Lv, L., Wang, W., Zhang, Z., Liu, X.: A novel intrusion detection system based on an optimal hybrid kernel extreme learning machine. Knowl. Based Syst. 195, 105648 (2020)
Malik, N.S., Collins, R., Vamburkar, M.: Cyberattack pings data systems of at least four gas networks (2018)
Mennenga, M., Cerdas, F., Thiede, S., Herrmann, C.: Exploring the opportunities of system of systems engineering to complement sustainable manufacturing and life cycle engineering. Procedia CIRP 80, 637–642 (2019)
Minerva, R., Lee, G.M., Crespi, N.: Digital twin in the IoT context: a survey on technical features, scenarios, and architectural models. Proc. IEEE 108(10), 1785–1824 (2020)
Mittal, S., Tolk, A., Pyles, A., Van Balen, N., Bergollo, K.: Digital twin modeling, co-simulation and cyber use-case inclusion methodology for IoT systems. In: Proceedings of the 2019 Winter Simulation Conference (WSC), pp. 2653–2664. IEEE (2019)
Mittal, S., Zeigler, B.P., Tolk, A., Õren, T.: Theory and practice of M&S in cyber environments. In: The Profession of Modeling and Simulation: Discipline, Ethics, Education, Vocation, Societies and Economics. Wiley Online Library (2017)
Mourtzis, D., Doukas, M., Bernidaki, D.: Simulation in manufacturing: review and challenges. Procedia CIRP 25, 213–229 (2014)
Parmar, R., Leiponen, A., Thomas, L.D.: Building an organizational digital twin. Bus. Horiz. 63(6), 725–736 (2020)
Pham, C., Tang, D., Chinen, K.i., Beuran, R.: CYRIS: a cyber range instantiation system for facilitating security training. In: Proceedings of the Seventh Symposium on Information and Communication Technology, pp. 251–258 (2016)
Piggin, R., Buffey, I.: Active defence using an operational technology honeypot (2016). https://bit.ly/3njohBz
Pokhrel, S.R., Garg, S.: Multipath communication with deep Q-Network for industry 4.0 automation and orchestration. IEEE Trans. Ind. Inform. 17(4), 2852–2859 (2020)
Pokhrel, S.R., Pan, L., Kumar, N., Doss, R., Le Vu, H.: Multipath TCP meets transfer learning: a novel edge-based learning for industrial IoT. IEEE Internet Things J. 8(13), 10299–10307 (2021)
Pokhrel, S.R., Qu, Y., Gao, L.: QoS-aware personalized privacy with multipath TCP for industrial IoT: analysis and design. IEEE Internet Things J. 7(6), 4849–4861 (2020)
Pokhrel, S.R., Vu, H.L., Cricenti, A.L.: Adaptive admission control for IoT applications in home wifi networks. IEEE Trans. Mob. Comput. 19(12), 2731–2742 (2019)
Polenghi, A., Fumagalli, L., Roda, I.: Role of simulation in industrial engineering: focus on manufacturing systems. IFAC Pap. OnLine 51(11), 496–501 (2018)
Poon, J., Jain, P., Konstantakopoulos, I.C., Spanos, C., Panda, S.K., Sanders, S.R.: Model-based fault detection and identification for switching power converters. IEEE Trans. Power Electron. 32(2), 1419–1430 (2016)
Roosta, T., Nilsson, D.K., Lindqvist, U., Valdes, A.: An intrusion detection system for wireless process control systems. In: Proceedings of the 2008 5th IEEE International Conference on Mobile ad hoc and Sensor Systems, pp. 866–872. IEEE (2008)
Rosenblatt, B., Trippe, B., Mooney, S., et al.: Digital Rights Management. New York (2002)
Rubio, J.E., Alcaraz, C., Roman, R., Lopez, J.: Analysis of intrusion detection systems in industrial ecosystems. In: SECRYPT, pp. 116–128 (2017)
Saad, A., Faddel, S., Youssef, T., Mohammed, O.A.: On the implementation of IoT-based digital twin for networked microgrids resiliency against cyber attacks. IEEE Trans. Smart Grid 11(6), 5138–5150 (2020)
Schinagl, S., Schoon, K., Paans, R.: A framework for designing a security operations centre (SOC). In: Proceedings of the 2015 48th Hawaii International Conference on System Sciences, pp. 2253–2262. IEEE (2015)
Shin, S., Kwon, T., Jo, G.Y., Park, Y., Rhy, H.: An experimental study of hierarchical intrusion detection for wireless industrial sensor networks. IEEE Trans. Ind. Inform. 6(4), 744–757 (2010)
Shultz, K.S., Wang, M., Olson, D.A.: Role overload and underload in relation to occupational stress and health. J. Int. Soc. Investig. Stress 26(2), 99–111 (2010)
Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., Sui, F.: Digital twin-driven product design, manufacturing and service with big data. Int. J. Adv. Manuf. Technol. 94(9), 3563–3576 (2018)
Tao, F., Zhang, H., Liu, A., Nee, A.Y.: Digital twin in industry: state-of-the-art. IEEE Trans. Ind. Inform. 15(4), 2405–2415 (2018)
Tao, F., Zhang, M.: Digital twin shop-floor: a new shop-floor paradigm towards smart manufacturing. IEEE Access 5, 20418–20427 (2017)
Tauber, M., Schmittner, C.: Enabling security and safety evaluation in industry 4.0 use cases with digital twins. ERCIM News (2018)
Tian, Z., et al.: A real-time correlation of host-level events in cyber range service for smart campus. IEEE Access 6, 35355–35364 (2018)
Tuptuk, N., Hailes, S.: Security of smart manufacturing systems. J. Manuf. Syst. 47, 93–106 (2018)
Tuyls, P., Akkermans, A.H.M., Kevenaar, T.A.M., Schrijen, G.-J., Bazen, A.M., Veldhuis, R.N.J.: Practical biometric authentication with template protection. In: Kanade, T., Jain, A., Ratha, N.K. (eds.) AVBPA 2005. LNCS, vol. 3546, pp. 436–446. Springer, Heidelberg (2005). https://doi.org/10.1007/11527923_45
Uhlemann, T.H.J., Lehmann, C., Steinhilper, R.: The digital twin: realizing the cyber-physical production system for industry 4.0. Procedia CIRP 61, 335–340 (2017)
Urias, V.E., Stout, W.M., Van Leeuwen, B., Lin, H.: Cyber range infrastructure limitations and needs of tomorrow: a position paper. In: Proceedings of the 2018 International Carnahan Conference on Security Technology (ICCST), pp. 1–5. IEEE (2018)
Vielberth, M., Menges, F., Pernul, G.: Human-as-a-security-sensor for harvesting threat intelligence. Cybersecurity 2(1), 1–15 (2019)
Vykopal, J., Ošlejšek, R., Čeleda, P., Vizvary, M., Tovarňák, D.: Kypo cyber range: design and use cases. In: Proceedings of the 12th International Conference on Software Technologies, pp. 310–321. SciTePress (2017)
Wayman, J., Jain, A., Maltoni, D., Maio, D.: An introduction to biometric authentication systems. In: Wayman, J., Jain, A., Maltoni, D., Maio, D. (eds.) Biometric Systems, pp. 1–20. Springer, London (2005). https://doi.org/10.1007/1-84628-064-8_1
Wei, D., Ji, K.: Resilient industrial control system (RICS): concepts, formulation, metrics, and insights. In: Proceedings of the 2010 3rd International Symposium on Resilient Control Systems, pp. 15–22. IEEE (2010)
Wurm, J., et al.: Introduction to cyber-physical system security: a cross-layer perspective. IEEE Trans. Multi Scale Comput. Syst. 3(3), 215–227 (2016)
Yahalom, R., Steren, A., Nameri, Y., Roytman, M., Porgador, A., Elovici, Y.: Improving the effectiveness of intrusion detection systems for hierarchical data. Knowl. Based Syst. 168, 59–69 (2019)
van Zadelhoff, M.: The biggest cybersecurity threats are inside your company. Harvard Bus. Rev. 19 (2016)
Zhang, J., Li, L., Lin, G., Fang, D., Tai, Y., Huang, J.: Cyber resilience in healthcare digital twin on lung cancer. IEEE Access 8, 201900–201913 (2020)
Zhao, Z., Shen, L., Yang, C., Wu, W., Zhang, M., Huang, G.Q.: IoT and digital twin enabled smart tracking for safety management. Comput. Oper. Res. 128, 105183 (2021)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Faleiro, R., Pan, L., Pokhrel, S.R., Doss, R. (2022). Digital Twin for Cybersecurity: Towards Enhancing Cyber Resilience. In: Xiang, W., Han, F., Phan, T.K. (eds) Broadband Communications, Networks, and Systems. BROADNETS 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 413. Springer, Cham. https://doi.org/10.1007/978-3-030-93479-8_4
Download citation
DOI: https://doi.org/10.1007/978-3-030-93479-8_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-93478-1
Online ISBN: 978-3-030-93479-8
eBook Packages: Computer ScienceComputer Science (R0)