Critical infrastructure represents important national assets for producing or distributing continuous flows of essential goods or services. When one aspect of the critical infrastructure shuts down due to an external disruption, other portions of the system that need those goods or services are likely to stop shortly thereafter, thus exacerbating the damage caused by the external disruption. Literature on critical infrastructure interdependency (CII) shows a need for analyzing failure records with time information from different types of critical infrastructure. This paper presents a knowledge discovery process for CII to extract records of frequent patterns of critical infrastructure failure that are directly or indirectly triggered by external disruptions. The knowledge discovery process, including integration of critical infrastructure failure records and their transformation into the data format needed by a data mining algorithm, is described. The paper includes a discussion on a disaster mitigation approach that could be used to stop CII-related failure events, and it includes the analysis of the results of sample critical infrastructure failure records. Disaster mitigation officials can employ the proposed approach to explore CII and to design countermeasures when a disaster hits.
|Number of pages||9|
|Journal||Journal of Computing in Civil Engineering|
|State||Published - Nov 2010|
- Data analysis
- Decision making