Skip to main content
SpringerLink
Log in

Cyber-attack detection in healthcare using cyber-physical system and machine learning techniques

  • Focus
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

Cyber-physical systems have been extensively utilized in healthcare domains to deliver high-quality patient treatment in multifaceted clinical scenarios. The medical device’ heterogeneity involved in these systems (mobile devices and body sensor nodes) introduces enormous attack surfaces and therefore necessitates effective security solutions for these complex environments. Hence, in this study, the cognitive machine learning assisted Attack Detection Framework has been proposed to share healthcare data securely. The Healthcare Cyber-Physical Systems will be proficient in spreading the collected data to cloud storage. Machine learning models predict cyber-attack behavior, and processing this data can offer healthcare specialists decision support. This proposed approach is based on a patient-centric design that safeguards the information on a trusted device like the end-users mobile phones and end-user control data sharing access. Experimental results demonstrate that our suggested model achieves an attack prediction ratio of 96.5%, an accuracy ratio of 98.2%, an efficiency ratio of 97.8%, less delay of 21.3%, and a communication cost of 18.9% to other existing models.

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.

Institutional subscriptions

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

  • Abdali-Mohammadi F, Meqdad MN, Kadry S (2020) Development of an IoT-based and cloud-based disease prediction and diagnosis system for healthcare using machine learning algorithms. Int J ArtifIntell ISSN 2252(8938):8938

    Google Scholar 

  • Al-Maitah M, AlZubi AA, Alarifi A (2019) An optimal storage utilization technique for IoT devices using sequential machine learning. Comput Netw 152:98-105

  • Al-Mhiqani MN, Ahmad R, Abidin ZZ, Ali NS, Abdulkareem KH (2019) Review of cyber attacks classifications and threats analysis in cyber-physical systems. Int J Technol Secur Trans 9(3):282–298

    Article  Google Scholar 

  • AlZubi AA (2019) An optimal sensor placement algorithm (O-SPA) for improving tracking precision of human activity in real-world healthcare systems. Comput Commun 148:98–105

    Article  Google Scholar 

  • Elhoseny M, Ramírez-González G, Abu-Elnasr OM, Shawkat SA, Arunkumar N, Farouk A (2018) Secure medical data transmission model for IoT-based healthcare systems. IEEE Access 6:20596–20608

    Article  Google Scholar 

  • Farivar F, Haghighi MS, Jolfaei A, Alazab M (2019) Artificial intelligence for detection, estimation, and compensation of malicious attacks in nonlinear cyber-physical systems and industrial IoT. .IEEE Trans Ind Inform 16(4):2716–2725

  • Gopalakrishnan T, Ruby D, Al-Turjman F, Gupta D, Pustokhina IV, Pustokhin DA, Shankar K (2020) Deep learning enabled data offloading withcyberattack detection model in mobile edge computing systems. IEEE Access 8:185938–185949

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

  • Haghighi MS, Farivar F, Jolfaei A, Tadayon MH (2020) Intelligent robust control for cyber-physical systems of rotary gantry type under denial of service attack. J Supercomput 76(4):3063–3085

    Article  Google Scholar 

  • Hassan MU, Rehmani MH, Chen J (2019) Differential privacy techniques for cyber physical systems: a survey. IEEE Commun Surv Tutor 22(1):746–789

  • Iqbal R, Doctor F, More B, Mahmudand S, Yousuf U (2020) big data analytics and computational intelligence for cyber–physical systems: recent trends and state of the art applications. Future Gener Comput Syst 105:766–778

  • Khan F, Ahamed J, Kadry S, Ramasamy LK (2020) Detecting malicious URLs using binary classification through ada boost algorithm. Int J Electr Comput Eng (2088–8708) 10

  • Kurde S, Shimpi J, Pawar R, Tingare B (2019) Cyber physical systems (CPS) and design automation for healthcare system: a new era of cyber computation for healthcare system. Structure 6(12)

  • Lee SJ, Yoo PD, Asyhari AT, Jhi Y, Chermak L, Yeunand CY, Taha K (2020) IMPACT: Impersonation attack detection via edge computing using deep autoencoder and feature abstraction. IEEE Access 8:65520–65529

    Article  Google Scholar 

  • Marques G, Miranda N, Kumar Bhoi A, Garcia-Zapirain B, Hamrioui S, de la Torre Díez I (2020) Internet of things and enhanced living environments: measuring and mapping air quality using cyber-physical systems and mobile computing technologies. Sensors 20(3):720

  • Meng W, Li W, Wang Y, Au MH (2020) Detecting insider attacks in medical cyber–physical networks based on behavioral profiling. Futur Gener Comput Syst 108:1258–1266

    Article  Google Scholar 

  • Poongodi M, Vijayakumar V, Al-Turjman F, Hamdi M, Ma M (2020) Intrusion prevention system for DDoS attack on VANET Withre CAPTCHA controller using information based metrics. IEEE Access 7:158481–158491

    Article  Google Scholar 

  • Qi L, Chen Y, Yuan Y, Fu S, Zhang X, Xu X (2020) A QoS-aware virtual machine scheduling method for energy conservation in cloud-based cyber-physical systems. World Wide Web 23(2):1275–1297

  • Qiu H, Qiu M, Liu M, Memmi G (2020) Secure health data sharing for medical cyber-physical systems for the healthcare 4.0. IEEE J Biomed Health Inform 24(9):2499–2505

    Article  Google Scholar 

  • Shakeel PM, Baskar S, Dhulipala VS, Mishra S, Jaber MM (2018) Maintaining security and privacy in health care system using learning based deep-Qnetworks. J Med Syst 42(10):186. https://doi.org/10.1007/s10916-018-1045-z

    Article  Google Scholar 

  • Shu H, Qi P, Huang Y, Chen F, Xie D, Sun L (2020) An efficient certificateless aggregate signature scheme for blockchain-based medical cyber physical systems. Sensors 20(5):1521

    Article  Google Scholar 

  • Shuwandy ML, Zaidan BB, Zaidan AA, Albahri AS, Alamoodi AH, Albahri OS, Alazab M (2020) mHealth authentication approach based 3D touchscreen and microphone sensors for real-time remote healthcare monitoring system, comprehensive review, open issues methodological aspects. Comp Sci Rev 38:100300

  • Sivakumar R (2020) Cyber victimization: healthcare cyber-physical systems (H-Cpss) vulnerability issues and challenges. Criminol Victimol Through Look Glass 155

  • Sliwa J (2019) Assessing complex evolving cyber-physical systems (case study: smart medical devices). Int J High Perform Comput Networking 13(3):294–303

    Article  Google Scholar 

  • Tang D, Tang L, Dai R, Chen J, Li X, Rodrigues JJ (2020) Mf-adaboost: Ldos attack detection based on multi-features and improved adaboost’. Futur Gener Comput Syst 106:347–359

    Article  Google Scholar 

  • Verma P, Sood SK, Kaur H (2020) A fog-cloud based cyber physical system for ulcerative colitis diagnosis and stage classification and management. Microprocess Microsyst 72:102929

  • Vijayakumar V, Priyan MK, Ushadevi G, Varatharajan R, Manogaran G, Tarare PV (2019) E-health cloud security using timing enabled proxy re-encryption. Mobile Netw Appl 24(3):1034–1045

    Article  Google Scholar 

  • Wang S, Lei T, Zhang L, Hsu CH, Yang F (2016) Offloading mobile data traffic for QoS-aware service provision in vehicular cyber-physical systems. Futur Gener Comput Syst 61:118–127

    Article  Google Scholar 

  • Wang S, Guo Y, Li Y, Hsu CH (2020) Cultural distance for service composition in cyber–physical–social system. Futur Gener Comput Syst 108:1049–1057

    Article  Google Scholar 

  • Wazid M, Reshma Dsouza P, Das AK, Bhat KV, Kumar N, Rodrigues JJ (2019) RAD‐EI: a routing attack detection scheme for edge‐based internet of things environment. Int J Commun Syst 32(15):e4024

  • weerakkody s, ozel o, mo y, sinopoli b (2017) resilient control in cyber-physical systems: countering uncertainty, constraints, and adversarial behavior. Found Trends® Syst Control 7(1–2):1–252

  • Wu D, Zhu H, Zhu Y, Chang V, He C, Hsu CH, Huang Z (2020) Anomaly detection based on RBM-LSTM neural network for CPS in advanced driver assistance system. ACM Trans Cyber-Phys Sys 4(3):1–17

  • Xu Z, He D, Vijayakumar P, Choo KKR, Li L (2020) Efficient NTRU lattice-based certificateless signature scheme for medical cyber-physical systems. J Med Syst 44(5):1–8

    Article  Google Scholar 

Download references

Acknowledgements

The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through research group No. (RG-1439-053).

Author information

Authors and Affiliations

  1. Computer Science Department, Community College, King Saud University, Riyadh, Saudi Arabia

    Ahmad Ali AlZubi, Mohammed Al-Maitah & Abdulaziz Alarifi

Authors
  1. Ahmad Ali AlZubi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohammed Al-Maitah
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Abdulaziz Alarifi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ahmad Ali AlZubi.

Ethics declarations

Conflicts of interest

The authors declare that they have no conflict of interests.

Additional information

Communicated by Vicente Garcia Diaz.

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

AlZubi, A.A., Al-Maitah, M. & Alarifi, A. Cyber-attack detection in healthcare using cyber-physical system and machine learning techniques. Soft Comput 25, 12319–12332 (2021). https://doi.org/10.1007/s00500-021-05926-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-021-05926-8

Keywords

Search

Navigation