Critical Infrastructure Asset Identification: Policy, Methodology and Gap Analysis - Archive ouverte HAL Access content directly
Conference Papers Year : 2016

Critical Infrastructure Asset Identification: Policy, Methodology and Gap Analysis

(1) , (1)
1
Christine Izuakor
  • Function : Author
  • PersonId : 1020648
Richard White
  • Function : Author
  • PersonId : 1020647

Abstract

Critical infrastructure asset identification is a core component of the risk management process. Amidst growing concerns of terrorist and natural disaster threats to the critical infrastructure, it is imperative that public and private sector stakeholders understand exactly which assets are critical to national security in order to prioritize risk management efforts. Challenges to accomplishing this task are the difficulty in identifying exactly which assets are critical and comparing the risks to assets across the many critical infrastructure sectors. A proven method for critical infrastructure asset identification that meets these needs does not exist today. This chapter explores the critical infrastructure protection policy frameworks and requirements of the United States, European Union and other countries, and summarizes the key requirements and methodologies. The methodologies are analyzed against the outlined requirements. Based on this analysis, a new approach is presented for critical infrastructure asset identification and additional research using multi-criteria decision theory is proposed to resolve the challenges that have limited progress in this area.
Fichier principal
Vignette du fichier
434671_1_En_2_Chapter.pdf (160.75 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01614862 , version 1 (11-10-2017)

Licence

Attribution - CC BY 4.0

Identifiers

Cite

Christine Izuakor, Richard White. Critical Infrastructure Asset Identification: Policy, Methodology and Gap Analysis. 10th International Conference on Critical Infrastructure Protection (ICCIP), Mar 2016, Arlington, VA, United States. pp.27-41, ⟨10.1007/978-3-319-48737-3_2⟩. ⟨hal-01614862⟩
111 View
1038 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More