AI and machine learning: A mixed blessing for cybersecurity
Source of Publication
2020 International Symposium on Networks, Computers and Communications, ISNCC 2020
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.
Institute of Electrical and Electronics Engineers Inc.
Computer networks; Machine learning; Attack vector; Cyber security; Cyber-attacks; Machine learning software; System faults; Wide spectrum; Security of data
Kamoun, Faouzi; Iqbal, Farkhund; Esseghir, Mohamed Amir; and Baker, Thar, "AI and machine learning: A mixed blessing for cybersecurity" (2020). All Works. 383.
Indexed in Scopus