3aRAM: A 3-Layer AHP-Based Risk Assessment Model and its Implementation for an Industrial IoT Cloud

Yu Lun Huang, Wen Lin Sun, Ying Han Tang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

To assist in the automation of factory processes, the amount of valuable data flow in the industrial cyber-physical system (CPS), Internet of things (IoT) and cloud computing will also have to increase accordingly. Thus, developing a risk assessment system which is specialized for an industrial IoT system is necessary, especially for the cloud platform that the data mainly flow on. In this paper, we revise the AHP (Analytic Hierarchy Process) method and propose a 3-layer AHP-based risk assessment model (3aRAM) for an Industrial IoT cloud (PaaS platform) to allow the cloud system to self-benchmark its own security status. The model is composed of three phases: data collection, data analysis and risk assessment. To refrain from unnecessary experts involving into the risk assessment phase, a feedback mechanism is designed in the proposed model. We realize the risk assessment system and apply it to an industrial IoT cloud system. Finally, we estimate the practicality of our system by injecting different degrees of noises and launching DoS attacks, and show the change of integrity and availability scores, which are generated by the proposed risk assessment model.

Original languageEnglish
Title of host publicationProceedings - Companion of the 19th IEEE International Conference on Software Quality, Reliability and Security, QRS-C 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages450-457
Number of pages8
ISBN (Electronic)9781728139258
DOIs
StatePublished - Jul 2019
Event19th IEEE International Conference on Software Quality, Reliability and Security Companion, QRS-C 2019 - Sofia, Bulgaria
Duration: 22 Jul 201926 Jul 2019

Publication series

NameProceedings - Companion of the 19th IEEE International Conference on Software Quality, Reliability and Security, QRS-C 2019

Conference

Conference19th IEEE International Conference on Software Quality, Reliability and Security Companion, QRS-C 2019
CountryBulgaria
CitySofia
Period22/07/1926/07/19

Keywords

  • analytic hierarchy process
  • cloud risk assessment
  • industrial internet-of-things

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