AI and machine learning: A mixed blessing for cybersecurity

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

doi:10.1109/ISNCC49221.2020.9297323

AI and machine learning: A mixed blessing for cybersecurity

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

School of Arch, Tech and Eng

Research output: Chapter in Book/Conference proceeding with ISSN or ISBN › Conference contribution with ISSN or ISBN › peer-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 language	English
Title of host publication	2020 International Symposium on Networks, Computers and Communications, ISNCC 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728156286
DOIs	https://doi.org/10.1109/ISNCC49221.2020.9297323
Publication status	Published - 20 Oct 2020
Event	2020 International Symposium on Networks, Computers and Communications, ISNCC 2020 - Montreal, Canada Duration: 20 Oct 2020 → 22 Oct 2020

Publication series

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

Conference

Conference	2020 International Symposium on Networks, Computers and Communications, ISNCC 2020
Country/Territory	Canada
City	Montreal
Period	20/10/20 → 22/10/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

Adversarial techniques
AI
Cybersecurity
Deep learning
Machine learning
Neural networks
Security

Access to Document

10.1109/ISNCC49221.2020.9297323

Cite this

Kamoun, F., Iqbal, F., Esseghir, M. A., & Baker, T. (2020). AI and machine learning: A mixed blessing for cybersecurity. In 2020 International Symposium on Networks, Computers and Communications, ISNCC 2020 Article 9297323 (2020 International Symposium on Networks, Computers and Communications, ISNCC 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISNCC49221.2020.9297323

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title = "AI and machine learning: A mixed blessing for cybersecurity",

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.",

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author = "Faouzi Kamoun and Farkhund Iqbal and Esseghir, {Mohamed Amir} and Thar Baker",

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doi = "10.1109/ISNCC49221.2020.9297323",

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Kamoun, F, Iqbal, F, Esseghir, MA & Baker, T 2020, AI and machine learning: A mixed blessing for cybersecurity. in 2020 International Symposium on Networks, Computers and Communications, ISNCC 2020., 9297323, 2020 International Symposium on Networks, Computers and Communications, ISNCC 2020, Institute of Electrical and Electronics Engineers Inc., 2020 International Symposium on Networks, Computers and Communications, ISNCC 2020, Montreal, Canada, 20/10/20. https://doi.org/10.1109/ISNCC49221.2020.9297323

AI and machine learning: A mixed blessing for cybersecurity. / Kamoun, Faouzi; Iqbal, Farkhund; Esseghir, Mohamed Amir et al.
2020 International Symposium on Networks, Computers and Communications, ISNCC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9297323 (2020 International Symposium on Networks, Computers and Communications, ISNCC 2020).

Research output: Chapter in Book/Conference proceeding with ISSN or ISBN › Conference contribution with ISSN or ISBN › peer-review

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AB - 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.

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KW - AI

KW - Cybersecurity

KW - Deep learning

KW - Machine learning

KW - Neural networks

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DO - 10.1109/ISNCC49221.2020.9297323

M3 - Conference contribution with ISSN or ISBN

AN - SCOPUS:85099583215

T3 - 2020 International Symposium on Networks, Computers and Communications, ISNCC 2020

BT - 2020 International Symposium on Networks, Computers and Communications, ISNCC 2020

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 20 October 2020 through 22 October 2020

ER -

Kamoun F, Iqbal F, Esseghir MA, Baker T. AI and machine learning: A mixed blessing for cybersecurity. In 2020 International Symposium on Networks, Computers and Communications, ISNCC 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9297323. (2020 International Symposium on Networks, Computers and Communications, ISNCC 2020). doi: 10.1109/ISNCC49221.2020.9297323

AI and machine learning: A mixed blessing for cybersecurity

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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