Examining Cybersecurity of Cyberphysical Systems for Critical Infrastructures Through Work Domain Analysis.

Examining Cybersecurity of Cyberphysical Systems for Critical Infrastructures Through Work Domain Analysis.

Wang, Hao;Lau, Nathan;Gerdes, Ryan M;
Human factors 2018 Vol. 60 pp. 699-718
230
wang2018examininghuman

Abstract

The aim of this study was to apply work domain analysis for cybersecurity assessment and design of supervisory control and data acquisition (SCADA) systems.Adoption of information and communication technology in cyberphysical systems (CPSs) for critical infrastructures enables automated and distributed control but introduces cybersecurity risk. Many CPSs employ SCADA industrial control systems that have become the target of cyberattacks, which inflict physical damage without use of force. Given that absolute security is not feasible for complex systems, cyberintrusions that introduce unanticipated events will occur; a proper response will in turn require human adaptive ability. Therefore, analysis techniques that can support security assessment and human factors engineering are invaluable for defending CPSs.We conducted work domain analysis using the abstraction hierarchy (AH) to model a generic SCADA implementation to identify the functional structures and means-ends relations. We then adopted a case study approach examining the Stuxnet cyberattack by developing and integrating AHs for the uranium enrichment process, SCADA implementation, and malware to investigate the interactions between the three aspects of cybersecurity in CPSs.The AHs for modeling a generic SCADA implementation and studying the Stuxnet cyberattack are useful for mapping attack vectors, identifying deficiencies in security processes and features, and evaluating proposed security solutions with respect to system objectives.Work domain analysis is an effective analytical method for studying cybersecurity of CPSs for critical infrastructures in a psychologically relevant manner.Work domain analysis should be applied to assess cybersecurity risk and inform engineering and user interface design.

Citation

ID: 31752
Ref Key: wang2018examininghuman
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
31752
Unique Identifier:
10.1177/0018720818769250
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet