Skip to main content
SpringerLink
Log in

Understanding the Cyber-Physical System in International Stadiums for Security in the Network from Cyber-Attacks and Adversaries using AI

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Sports stadiums have a substantial influence on the environmental, urban, and social context. Information and communication technology applications in the international sports stadium increasingly use modern venues and facilities, containing the command and control system, intelligent application of sports facilities, television systems, ticket access control systems, communication systems for event management, contest information systems, etc. There is a high demand for advanced stadium security systems because of the large number of sporting events organized. Hence, in this study, an Artificial intelligence assisted Cyber-Physical System (AI-CPS) has been proposed for security in the network to predict cyber attacks and adversaries. The data has been collected and analyzed, and the proposed AI-CPS model predicts anomaly behaviour in the network. This study deals with the subject of how surveillance and security practices at sports events are organized. Advances in Artificial Intelligence (AI) techniques show potential in enabling cybersecurity authorities to counter the ever-evolving attack posed by an adversary. Here, this paper explores AI’s potential in enhancing cybersecurity resolutions by determining both its strengths and weaknesses. The numerical results show that the suggested AI-CPS model improves an accuracy ratio of 95.6%, a prediction ratio of 97.6%, packet loss of 12.3%, delay ratio of 15.1%, and latency ratio of 11.2% to other existing methods.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Raj, E. D., Manogaran, G., Srivastava, G., & Wu, Y. (2020). Information Granulation-Based Community Detection for Social Networks. IEEE Transactions on Computational Social Systems.

  2. Wei, W., Guizani, M., Ahmed, S. H., & Zhu, C. (2020). Guest Editorial: Special Section on Integration of Big Data and Artificial Intelligence for Internet of Things.

  3. Farouk, A., Batle, J., Elhoseny, M., Naseri, M., Lone, M., Fedorov, A., & Abdel-Aty, M. (2018). Robust general N user authentication scheme in a centralized quantum communication network via generalized GHZ states. Frontiers of Physics, 13(2), 130306

    Article  Google Scholar 

  4. Khan, W. U., Liu, J., Jameel, F., Khan, M. T. R., Ahmed, S. H., &Jäntti, R. (2020). Secure backscatter communications in multi-Cell NOMA networks: Enabling link security for massive IoT networks. IEEE INFOCOM 2020-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) (pp. 213–218). IEEE.

  5. Chaudhry, S. A., Shon, T., Al-Turjman, F., & Alsharif, M. H. (2020). Correcting design flaws: An improved and cloud assisted vital agreement scheme in cyber-physical systems. Computer Communications, 153, 527–537

    Article  Google Scholar 

  6. Gupta, R., Tanwar, S., Al-Turjman, F., Italiya, P., Nauman, A., & Kim, S. W. (2020). Smart contract privacy protection using AI in cyber-physical systems: Tools, techniques and challenges. IEEE Access, 8, 24746–24772

    Article  Google Scholar 

  7. Shankar, A., Jaisankar, N., Khan, M. S., Patan, R., & Balamurugan, B. (2018). A hybrid model for security-aware cluster head selection in wireless sensor networks. IET Wireless Sensor Systems, 9(2), 68–76

    Article  Google Scholar 

  8. Shanker, R., Luhach, A. K., & Sardar, A. (2016). To enhance the security in wireless nodes using centralized and synchronized IDS technique. Indian Journal of Science and Technology, 9(32), 1–5

    Article  Google Scholar 

  9. Prasad, S. K., Rachna, J., Khalaf, O. I., & Le, D. N. (2020). Map matching algorithm: Real time location tracking for smart security application. Telecommunications and Radio Engineering, 79(13), 1189–1203

    Article  Google Scholar 

  10. Ogudo, K. A., Muwawa Jean Nestor, D., Ibrahim Khalaf, O., & DaeiKasmaei, H. (2019). A device performance and data analytics concept for smartphones’ IoT services and machine-type communication in cellular networks. Symmetry, 11(4), 593

    Article  Google Scholar 

  11. Khalaf, O. I., Abdulsahib, G. M., Kasmaei, H. D., & Ogudo, K. A. (2020). A new algorithm on the application of blockchain technology in live stream video transmissions and telecommunications. International Journal of e-Collaboration (IJeC), 16(1), 16–32

    Article  Google Scholar 

  12. Manogaran, G., Rawal, B. S., Saravanan, V., Kumar, P. M., Martínez, O. S., Crespo, R. G., & Krishnamoorthy, S. (2020). Blockchain based integrated security measure for reliable service delegation in 6G communication environment. Computer Communications, 161, 248–256

    Article  Google Scholar 

  13. Herrera-Cubides, J. F., Gaona-García, P. A., Montenegro-Marín, C., Cataño, D., & González-Crespo, R. (2019). Security aspects in web of data based on trust principles a brief of literature review. International Journal of Communication Networks and Information Security, 11(3), 365–379

    Google Scholar 

  14. Wang, G. G., Cai, X., Cui, Z., Min, G., & Chen, J. (2017). High-performance computing for cyber-physical social systems by using evolutionary multi-objective optimization algorithm. IEEE Transactions on Emerging Topics in Computing.

  15. Mirakhorli, M., Galster, M., & Williams, L. (2020). Understanding software security from design to deployment. ACM SIGSOFT Software Engineering Notes, 45(2), 25–26

    Article  Google Scholar 

  16. Chaudhry, S. A., Shon, T., Al-Turjman, F., & Alsharif, M. H. (2020). Correcting design flaws: An improved and cloud assisted key agreement scheme in cyber physical systems. Computer Communications, 153, 527–537

    Article  Google Scholar 

  17. Lin, H., Alemzadeh, H., Kalbarczyk, Z., & Iyer, R. (2020). Challenges and opportunities in the detection of safety-critical cyberphysical attacks. Computer, 53(3), 26–37

    Article  Google Scholar 

  18. Shin, S. Y., Chaouch, K., Nejati, S., Sabetzadeh, M., Briand, L. C., & Zimmer, F. (2020). Uncertainty-aware specification and analysis for hardware-in-the-loop testing of cyber-physical systems. Journal of Systems and Software, 171, 110813

    Article  Google Scholar 

  19. Hachem, J. E., Chiprianov, V., Babar, M. A., Khalil, T. A., & Aniorte, P. (2020). Modeling, analyzing and predicting security cascading attacks in smart buildings systems-of-systems. Journal of Systems and Software, 162, 110484

    Article  Google Scholar 

  20. Kozjek, D., Vrabič, R., Rihtaršič, B., Lavrač, N., & Butala, P. (2020). Advancing manufacturing systems with big-data analytics: A conceptual framework. International Journal of Computer Integrated Manufacturing, 33(2), 169–188

    Article  Google Scholar 

  21. Bucchiarone, A., Cabot, J., Paige, R. F., & Pierantonio, A. (2020). Grand challenges in model-driven engineering: An analysis of the state of the research. Software and Systems Modeling, 19(1), 5–13

    Article  Google Scholar 

  22. Kholod, M. V., Ponomarev, S. V., & Gorlova, E. A. (2020). Artificial intelligence and its impact on economic security: Trends, estimates and forecasts. Scientific and Technical Revolution: Yesterday, Today and Tomorrow, 129, 213

    Google Scholar 

  23. Wang, B., Sun, Y., Duong, T. Q., Nguyen, L. D., & Zhao, N. (2020). Security enhanced content sharing in social IoT: A directed hypergraph-based learning scheme. IEEE Transactions on Vehicular Technology, 69(4), 4412–4425

    Article  Google Scholar 

  24. Fang, X., Xu, M., Xu, S., & Zhao, P. (2019). A deep learning framework for predicting cyber attacks rates. EURASIP Journal on Information Security, 2019(1), 5

    Article  Google Scholar 

  25. Ge, X., Han, Q. L., Zhang, X. M., Ding, D., & Yang, F. (2020). Resilient and secure remote monitoring for a class of cyber-physical systems against attacks. Information Sciences, 512, 1592–1605

    Article  MathSciNet  MATH  Google Scholar 

  26. Darbandi, F., Jafari, A., Karimipour, H., Dehghantanha, A., Derakhshan, F., & Choo, K. K. R. (2020). Real-time stability assessment in smart cyber-physical grids: A deep learning approach. IET Smart Grid, 3(4), 454–461

    Article  Google Scholar 

  27. Bhati, B. S., Rai, C. S., Balamurugan, B., & Al-Turjman, F. (2020). An intrusion detection scheme based on the ensemble of discriminant classifiers. Computers & Electrical Engineering, 86, 106742

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Physical Education, Shaanxi Normal University, Xi’an, 710062, Shanxi, China

    Bingjun Wan & Chengwei Xu

  2. Department of Computer Science and Engineering, SRM Institute of Science and Technology, Delhi NCR Campus, Ghaziabad, Uttar Pradesh, 201204, India

    Rajendra Prasad Mahapatra

  3. Department of Information Technology, School of Computing, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur, Chennai, Tamil Nadu, 603203, India

    P. Selvaraj

Authors
  1. Bingjun Wan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chengwei Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rajendra Prasad Mahapatra
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. P. Selvaraj
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bingjun Wan.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wan, B., Xu, C., Mahapatra, R.P. et al. Understanding the Cyber-Physical System in International Stadiums for Security in the Network from Cyber-Attacks and Adversaries using AI. Wireless Pers Commun 127, 1207–1224 (2022). https://doi.org/10.1007/s11277-021-08573-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-021-08573-2

Keywords

Search

Navigation