This repository provides an open source codebase to quantify the direct and indirect impacts of infrastructure cascading failure. For example, resulting from a cyber-attack.
The repository name is taken from Wonder Woman where Osira is a fictional Egyptian Goddess respected for her advanced understanding of technology.
Improving our understanding of the groups of technologies known as 'infrastructure systems' can help us make better decisions, particularly in relation to risk management.
Despite infrastructure being of growing importance, there are surprisingly few open source, fully-tested, fully-documented codebases available for risk analysts to use. The contribution of this repository is to fill this gap.
- Oughton, E. J. et al. (2019) Stochastic Counterfactual Risk Analysis for the Vulnerability Assessment of Cyber-Physical Attacks on Electricity Distribution Infrastructure Networks, Risk Analysis, 39(9), pp. 2012–2031. https://doi.org/10.1111/risa.13291.
- Kelly, S. et al. (2016) Integrated Infrastructure: Cyber Resiliency in Society, Mapping the Consequences of an Interconnected Digital Economy. Cambridge: Cambridge Centre for Risk Studies.
The recommended installation method for osira is to use conda, which handles packages and
virtual environments, along with the conda-forge channel which has a host of pre-built
libraries and packages.
Create a conda environment called osira:
conda create --name osira python=3.7 gdal
Activate it (run this each time you switch projects):
conda activate osira
You need to install necessary packages:
conda install geopandas pytest matplotlib seaborn
Then clone this repository and run:
python setup.py install
Or if you want to develop the package:
python setup.py develop
And if you want to check test coverage run pytest:
python -m pytest
To quickly get started using synthetic data run this:
python scripts/demo.py
Followed by using the vis.py script to visualize the results:
python vis/vis.py
The approach has been developed over many years at numerous institutions:
- 2015-2017: Cambridge Centre for Risk Studies, University of Cambridge
- 2017-2020: Environmental Change Institute, University of Oxford
- 2020-2021: Geography and Geoinformation Sciences, George Mason University
We would like to thank UKRI, specifically the Engineering and Physical Sciences Research Council for support via grant EP/N017064/1.
- Ed Oughton (GMU & Oxford)
- Daniel Ralph (Cambridge)
- Eireann Leverett (Cambridge & Airbus)
- Raghav Pant (Oxford)
- Jen Copic (Cambridge)
- Simon Ruffle (Cambridge)
- Andrew Coburn (Cambridge)
- Michele Tuveson (Cambridge)
- Scott Thacker (Oxford & UNOPS)
- Jim Hall (Oxford)
- Scott Kelly (Cambridge & UTS)