Towards trustworthy Artificial Intelligence: Security risk assessment methodology for Artificial Intelligence systems

Eider Iturbe*, Erkuden Rios, Nerea Toledo

*Corresponding author for this work

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

Abstract

The digitalization and smartization of modern digital systems include the implementation and integration of emerging innovative technologies, such as Artificial Intelligence. By incorporating new technologies, the surface attack of the system also expands, and specialized cybersecurity mechanisms and tools are required to counter the potential new threats. This paper introduces a holistic security risk assessment methodology that aims to assist Artificial Intelligence system stakeholders guarantee the correct design and implementation of technical robustness in Artificial Intelligence systems. The methodology is designed to facilitate the automation of the security risk assessment of Artificial Intelligence components together with the rest of the system components. Supporting the methodology, the solution to the automation of Artificial Intelligence risk assessment is also proposed. Both the methodology and the tool will be validated when assessing and treating risks on Artificial Intelligence-based cybersecurity solutions integrated in modern digital industrial systems that leverage emerging technologies such as cloud continuum including Software-defined networking (SDN).

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2023
PublisherIEEE Computer Society
Pages291-297
Number of pages7
ISBN (Electronic)9798350339826
DOIs
Publication statusPublished - 2023
Event14th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2023 - Naples, Italy
Duration: 4 Dec 20236 Dec 2023

Publication series

NameProceedings of the International Conference on Cloud Computing Technology and Science, CloudCom
ISSN (Print)2330-2194
ISSN (Electronic)2330-2186

Conference

Conference14th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2023
Country/TerritoryItaly
CityNaples
Period4/12/236/12/23

Keywords

  • Artificial Intelligence
  • Cyber Security
  • Risk Assessment
  • Technical robustness
  • Trustworthy

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