Article
AI and machine learning: A mixed blessing for cybersecurity
2020 International Symposium on Networks, Computers and Communications, ISNCC 2020
Document Type
Conference Proceeding
Publication Date
10-20-2020
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.
DOI Link
10.1109/isncc49221.2020.9297323
ISBN
9780000000000
Publisher
Institute of Electrical and Electronics Engineers Inc.
Disciplines
Keywords
- Computer networks,
- Machine learning,
- Attack vector,
- Cyber security,
- Cyber-attacks,
- Machine learning software,
- System faults,
- Wide spectrum,
- Security of data
Scopus ID
85099583215
Indexed in Scopus
Yes
Open Access
No
https://doi.org/10.1109/isncc49221.2020.9297323
Citation Information
Faouzi Kamoun, Farkhund Iqbal, Mohamed Amir Esseghir and Thar Baker. "AI and machine learning: A mixed blessing for cybersecurity" 2020 International Symposium on Networks, Computers and Communications, ISNCC 2020 (2020) Available at: http://works.bepress.com/farkhund-iqbal/112/