- By:
- Devineni, Pravallika ; Kay, William W; Lu, Hao ; Tabassum, Anika; Chinthavali, Supriya ; Lee, Sangkeun M
- Page Number:
- 2884-2890
- Issue Number:
- 978-1-7281
- Book Title:
- 2020 IEEE International Conference on Big Data (Big Data)
- Publication Date:
- December 27, 2023
- Publisher Location:
- IEEE, Georgia, United States of America
- Conference Name:
- BTSD 2020 : The 2nd International Workshop on Big Data Tools, Methods, and Use Cases for Innovative Scientific Discovery (BTSD) 2020
- Conference Location:
- Atlanta, Georgia, United States of America
- Conference Sponsor:
- IEEE
- View DOI Listing:
- https://doi.org/10.1109/BigData50022.2020.9377730
Abstract
Modern society is increasingly dependent on the stability of a complex system of interdependent infrastructure sectors. Vulnerability in critical infrastructures (CIs) is defined as a measure of system susceptibility to threat scenarios. Quantifying vulnerability in CIs has not been adequately addressed in the literature. This paper presents ongoing research on how the authors model CIs as network-based models and propose a set of metrics to quantify vulnerability in CI systems. The size and complexity of the CIs make this a challenging task. These metrics could be used for planning and efficient decision-making during extreme events.
