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