Skip to main content
SpringerLink
Log in

A control-driven autonomous authentication scheme for peer-to-peer control systems assisted industrial Internet of things

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

Abstract

Peer-to-Peer (P2P) networks are prominent in the Internet-of-things-assisted industrial environments for distributed computing and smart control systems. The problem arises with the independence and peer systems security due to anonymous access and security measures. In this paper, an innovative control-driven autonomous authentication scheme is proposed for improving the access security of P2P industrial systems. The proposed scheme provides authentication based on P2P system control requirements within its access time. The P2P control systems and their functionalities are provided with classified security measures for administering autonomous security. The advantage of offering autonomous protection is to prevent the sequence of security breaches and control sabotage. In this process, the control system requirements and authentications are paired by identifying the machines' operating time and access time. For identification and grouping-based classification, support vector machines are used. It learns the sabotage and control requirements based on access and control time for providing a rupture-less industrial process. It helps to leverage the detection of autonomous adversaries in P2P industrial control systems. Besides, a less complex and latent-free security measure is achievable using the proposed scheme.

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
Figure 4
Figure 5
Figure 6
Figure 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  • AA AlZubi, A Alarifi, M Al-Maitah, O Alheyasat (2020) Multi-sensor information fusion for Internet of Things assisted automated guided vehicles in smart city. Sustain Cities Soc, online version, pp 102539.

  • Abuhasel KA, Khan MA (2020) A secure industrial internet of things (IIoT) framework for resource management in smart manufacturing. IEEE Access 8:117354–117364

    Article  Google Scholar 

  • Ahmad Ali AlZubi (2019) Location assisted delay-less service discovery method for IoT environments. Comput Commun 150:405–412

    Article  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

    Article  Google Scholar 

  • Al-Turjman F, Alturjman S (2018) Context-sensitive access in industrial internet of things (IIoT) healthcare applications. IEEE Trans Industr Inf 14(6):2736–2744

    Article  Google Scholar 

  • AlZubi AA, Al-Maitah M, Alarifi A (2019) A best-fit routing algorithm for non-redundant communication in large-scale. IoT Based Netw 152:106–113

    Google Scholar 

  • Baskaran SBM, Raja G, Bashir AK, Murata M (2017) QoS-aware frequency-based 4G+relative authentication model for next generation LTE and its dependent public safety networks. IEEE Access 5:21977–21991

    Article  Google Scholar 

  • Boyes H, Hallaq B, Cunningham J, Watson T (2018) The industrial internet of things (IIoT): an analysis framework. Comput Ind 101:1–12

    Article  Google Scholar 

  • Cao, Y., Jia, F., & Manogaran, G. (2019). Efficient traceability systems of steel products Using Blockchain-based Industrial Internet of Things. IEEE Transactions on Industrial Informatics

  • Chen S, Yang L, Zhao C, Varadarajan V, Wang K (2020) Double-blockchain assisted secure and anonymous data aggregation for fog-enabled smart grid. Engineering

  • Das AK, Wazid M, Kumar N, Vasilakos AV, Rodrigues JJ (2018) Biometrics-based privacy-preserving user authentication scheme for cloud-based industrial Internet of Things deployment. IEEE Internet Things J 5(6):4900–4913

    Article  Google Scholar 

  • Deep S, Zheng X, Jolfaei A, Yu D, Ostovari P, Bashir AK (March 2020) A survey of security and privacy issues in the Internet of Things from the layered context. Wiley, Transactions on Emerging Telecommunications Technologies

    Book  Google Scholar 

  • Gebremichael T, Ledwaba LP, Eldefrawy MH, Hancke GP, Pereira N, Gidlund M, Akerberg J (2020) Security and privacy in the industrial internet of things: current standards and future challenges. IEEE Access 8:152351–152366

    Article  Google Scholar 

  • George G, Thampi SM (2018) A graph-based security framework for securing industrial IoT networks from vulnerability exploitations. IEEE Access 6:43586–43601

    Article  Google Scholar 

  • Guido Dartmann, Houbing Song, and Anke Schmeink. Big Data Analytics for Cyber-Physical Systems: Machine Learning for the Internet of Things. ISBN: 9780128166376. Elsevier, 2019, pp. 1–360.

  • Hassan MM, Gumaei A, Huda S, Almogren A (2020) Increasing the trustworthiness in the industrial IoT networks through a reliable cyberattack detection model. IEEE Trans Ind Inf 16(9):6154–6162

    Article  Google Scholar 

  • Huang K, Zhang X, Mu Y, Wang X, Yang G, Du X, Guizani M (2019) Building redactable consortium blockchain for industrial Internet-of-Things. IEEE Trans Industr Inf 15(6):3670–3679

    Article  Google Scholar 

  • Lee Y, Lee KM, Lee SH (2019) Blockchain-based reputation management for custom manufacturing service in the peer-to-peer networking environment. Peer Peer Network Appl 13(2):671–683

    Article  Google Scholar 

  • Li X, Niu J, Bhuiyan MZA, Wu F, Karuppiah M, Kumari S (2018) A robust ECC-based provable secure authentication protocol with privacy preserving for industrial internet of things. IEEE Trans Ind Inf 14(8):3599–3609

    Article  Google Scholar 

  • McNinch M, Parks D, Jacksha R, Miller A (2019) Leveraging IIoT to improve machine safety in the mining industry. Min Metall Explor 36(4):675–681

    Google Scholar 

  • Mosteiro-Sanchez A, Barcelo M, Astorga J, Urbieta A (2020) Securing IIoT using defence-in-depth: towards an end-to-end secure industry 4.0. J Manuf Syst 57:367–378

    Article  Google Scholar 

  • Plaga S, Wiedermann N, Anton SD, Tatschner S, Schotten H, Newe T (2019) Securing future decentralised industrial IoT infrastructures: challenges and free open source solutions. Futur Gener Comput Syst 93:596–608

    Article  Google Scholar 

  • Qureshi KN, Rana SS, Ahmed A, Jeon G (2020) A novel and secure attacks detection framework for smart cities industrial internet of things. Sustain Cities Soc 61

  • Sabina Jeschke, Christian Brecher, Houbing Song, and Danda Rawat, Industrial Internet of Things: Cybermanufacturing Systems. ISBN: 978–3–319–42558–0, Cham, Switzerland: Springer, 2017, pp. 1–715.

  • Shen M, Liu H, Zhu L, Xu K, Yu H, Du X, Guizani M (2020) Blockchain-assisted secure device authentication for cross-domain industrial IoT. IEEE J Select Areas Commun 38(5):942–954

    Article  Google Scholar 

  • Shijie W, Yingfeng Z (2020) A credit-based dynamical evaluation method for the smart configuration of manufacturing services under Industrial Internet of Things. J Intell Manuf

  • Sodhro AH, Pirbhulal S, Muzammal M, Zongwei L (2020) Towards blockchain-enabled security technique for industrial internet of things based decentralized applications. J Grid Comput, pp 1–14.

  • Sundarasekar R, Shakeel PM, Baskar S, Kadry S, Mastorakis G, Mavromoustakis CX, Gn V (2019) Adaptive energy aware quality of service for reliable data transfer in under water acoustic sensor networks. IEEE Access 7: 80093–80103

  • Tajalli SZ, Mardaneh M, Taherian-Fard E, Izadian A, Kavousi-Fard A, Dabbaghjamanesh M, Niknam T (2020) DoS-resilient distributed optimal scheduling in a fog supporting IIoT-based smart microgrid. IEEE Trans Ind Appl 56(3):2968–2977

    Article  Google Scholar 

  • Wang EK, Liang Z, Chen C-M, Kumari S, Khan MK (2020) PoRX: a reputation incentive scheme for blockchain consensus of IIoT. Future Gener Comput Syst 102:140–151

    Article  Google Scholar 

  • Xu X, Han M, Nagarajan SM, Anandhan P (2020) Industrial Internet of Things for smart manufacturing applications using hierarchical trustful resource assignment. Comput Commun 160:423–430

    Article  Google Scholar 

  • Xu Y, Ren J, Wang G, Zhang C, Yang J, Zhang Y (2019) A blockchain-based nonrepudiation network computing service scheme for industrial IoT. IEEE Trans Ind Inf 15(6):3632–3641

    Article  Google Scholar 

  • Yan X, Xu Y, Xing X, Cui B, Guo Z, Guo T (2020) Trustworthy network anomaly detection based on an adaptive learning rate and momentum in IIoT. IEEE Trans Ind Inf 16(9):6182–6192

    Article  Google Scholar 

  • Zhang D, Chan CC, Zhou GY (2018) Enabling Industrial Internet of Things (IIoT) towards an emerging smart energy system. Global Energy Interconnect 1(1):39–47

    Google Scholar 

  • Zhu F, Wu W, Zhang Y, Chen X (2019) Privacy-preserving authentication for general directed graphs in industrial IoT. Inf Sci 502:218–228

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

Researchers would like to thank Scientific Research, Qassim University, for funding this project's publication.

Author information

Authors and Affiliations

  1. Department of Computer, College of Science and Arts in Ar Rass, Qassim University, Ar Rass, Saudi Arabia

    Salem Alkhalaf

Authors
  1. Salem Alkhalaf
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Salem Alkhalaf.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

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

Alkhalaf, S. A control-driven autonomous authentication scheme for peer-to-peer control systems assisted industrial Internet of things. Soft Comput 25, 12175–12189 (2021). https://doi.org/10.1007/s00500-021-05883-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-021-05883-2

Keywords

Search

Navigation