AI and machine learning: A mixed blessing for cybersecurity

Faouzi Kamoun, Farkhund Iqbal, Mohamed Amir Esseghir, Thar Baker

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBNpeer-review

Abstract

While the usage of Artificial Intelligence and Machine Learning Software (AI/MLS) in defensive cybersecurity has received considerable attention, there remains a noticeable research gap on their offensive use. This paper reviews the defensive usage of AI/MLS in cybersecurity and then presents a survey of its offensive use. Inspired by the System-Fault-Risk (SFR) framework, we categorize AI/MLS-powered cyberattacks by their actions into seven categories. We cover a wide spectrum of attack vectors, discuss their practical implications and provide some recommendations for future research.

Original languageEnglish
Title of host publication2020 International Symposium on Networks, Computers and Communications, ISNCC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728156286
DOIs
Publication statusPublished - 20 Oct 2020
Event2020 International Symposium on Networks, Computers and Communications, ISNCC 2020 - Montreal, Canada
Duration: 20 Oct 202022 Oct 2020

Publication series

Name2020 International Symposium on Networks, Computers and Communications, ISNCC 2020

Conference

Conference2020 International Symposium on Networks, Computers and Communications, ISNCC 2020
Country/TerritoryCanada
CityMontreal
Period20/10/2022/10/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

  • Adversarial techniques
  • AI
  • Cybersecurity
  • Deep learning
  • Machine learning
  • Neural networks
  • Security

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