Abstract
It is highly complex for organizations to navigate the emerging cybersecurity landscape due to the lack of available decision-support tools. In this chapter, we present a systematic approach to supply chain risk mitigating decision-making in IoT systems and networks. The framework discovers relationships between suppliers and service providers across the different interconnected devices and provides an analysis of the associated cyber risks including the weakest and most vulnerable links. The decision-support engine allows for planning new system deployments from a supply chain viewpoint by recommending an optimized selection of suppliers.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
C.K. Wu, K.F. Tsang, Y. Liu, H. Zhu, Y. Wei, H. Wang, T.T. Yu, Supply chain of things: A connected solution to enhance supply chain productivity. IEEE Commun. Mag. 57(8), 78–83 (2019)
T. Kieras, J. Farooq, Q. Zhu, I-SCRAM: A framework for IoT supply chain risk analysis and mitigation decisions. IEEE Access 9, 29827–29840 (2021)
H.P. Ho, The supplier selection problem of a manufacturing company using the weighted multi-choice goal programming and MINMAX multi-choice goal programming. Appl. Math. Model. 75, 819–836 (2019). [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0307904X19303610
Network Defense Mechanisms Against Malware Infiltration (Wiley, 2021), ch. 8, pp. 97–124 [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10.1002/9781119716112.ch8
J. Farooq, Q. Zhu, Internet of Things-Enabled Systems and Infrastructure (Wiley, 2021), ch. 1, pp. 1–8. [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10.1002/9781119716112.ch1
H.Y. Mak, Z.J. Shen, Risk diversification and risk pooling in supply chain design. IIE Trans. 44(8), 603–621 (2012)
M.J. Farooq, Q. Zhu, Modeling, analysis, and mitigation of dynamic botnet formation in wireless IoT networks. IEEE Trans. Inf. Forens. Secur. 14(9), 2412–2426 (2019)
J. Farooq, Q. Zhu, Resource Management in IoT-Enabled Interdependent Infrastructure (Wiley, 2021), ch. 2, pp. 9–13. [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10.1002/9781119716112.ch2
A. Rauzy, Toward an efficient implementation of the MOCUS algorithm, IEEE Trans. Reliab. 52(2), 175–180 (2003)
M. Todinov, Methods for analysis of complex reliability networks, in Risk-Based Reliability Analysis and Generic Principles for Risk Reduction (Elsevier, 2007), pp. 31–58
Author information
Authors and Affiliations
Corresponding authors
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Kieras, T., Farooq, J., Zhu, Q. (2022). Risk Mitigation Decisions. In: IoT Supply Chain Security Risk Analysis and Mitigation. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-031-08480-5_3
Download citation
DOI: https://doi.org/10.1007/978-3-031-08480-5_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-08479-9
Online ISBN: 978-3-031-08480-5
eBook Packages: Computer ScienceComputer Science (R0)