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On Data Integrity Attacks against Industrial Internet of Things

Conference Paper


Abstract


  • Industrial Internet of Things (IIoT) is predicted to drive the fourth industrial revolution through massive interconnection of industrial devices, integrating advances in smart machinery and data analytics driven by computing, networking and artificial intelligence techniques. The massive interconnections between industrial devices increase not only information exchange, productivity, and resource efficiency, but also cybersecurity risks and their impact on the Industrial Internet of Things (IIoT) system. In this paper, we investigate the evolutionary process, which captures the natural interactions and evolutions of both attackers and defenders, as well as their strategies to launch data integrity attacks and protect the IIoT system, respectively. We leverage the wireless cyber-physical simulator (WCPS) as a realistic IIoT environment to implement and evaluate strategies at different levels of evolution. The experimental results indicate the effectiveness of defensive strategies in guarding against various forms of data integrity attacks with increase in time and knowledge throughout the evolutionary process.

Publication Date


  • 2020

Citation


  • Xu, H., Yu, W., Liu, X., Griffith, D., & Golmie, N. (2020). On Data Integrity Attacks against Industrial Internet of Things. In Proceedings - IEEE 18th International Conference on Dependable, Autonomic and Secure Computing, IEEE 18th International Conference on Pervasive Intelligence and Computing, IEEE 6th International Conference on Cloud and Big Data Computing and IEEE 5th Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020 (pp. 21-28). doi:10.1109/DASC-PICom-CBDCom-CyberSciTech49142.2020.00020

Scopus Eid


  • 2-s2.0-85097639947

Web Of Science Accession Number


Start Page


  • 21

End Page


  • 28

Abstract


  • Industrial Internet of Things (IIoT) is predicted to drive the fourth industrial revolution through massive interconnection of industrial devices, integrating advances in smart machinery and data analytics driven by computing, networking and artificial intelligence techniques. The massive interconnections between industrial devices increase not only information exchange, productivity, and resource efficiency, but also cybersecurity risks and their impact on the Industrial Internet of Things (IIoT) system. In this paper, we investigate the evolutionary process, which captures the natural interactions and evolutions of both attackers and defenders, as well as their strategies to launch data integrity attacks and protect the IIoT system, respectively. We leverage the wireless cyber-physical simulator (WCPS) as a realistic IIoT environment to implement and evaluate strategies at different levels of evolution. The experimental results indicate the effectiveness of defensive strategies in guarding against various forms of data integrity attacks with increase in time and knowledge throughout the evolutionary process.

Publication Date


  • 2020

Citation


  • Xu, H., Yu, W., Liu, X., Griffith, D., & Golmie, N. (2020). On Data Integrity Attacks against Industrial Internet of Things. In Proceedings - IEEE 18th International Conference on Dependable, Autonomic and Secure Computing, IEEE 18th International Conference on Pervasive Intelligence and Computing, IEEE 6th International Conference on Cloud and Big Data Computing and IEEE 5th Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020 (pp. 21-28). doi:10.1109/DASC-PICom-CBDCom-CyberSciTech49142.2020.00020

Scopus Eid


  • 2-s2.0-85097639947

Web Of Science Accession Number


Start Page


  • 21

End Page


  • 28