AI and machine learning: A mixed blessing for cybersecurity
Faouzi Kamoun, Farkhund Iqbal, Mohamed Amir Esseghir, Thar Baker
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.
Topics & Concepts
OffensiveComputer scienceComputer securityCategorizationHoneypotCover (algebra)Artificial intelligenceSoftwareBlessingEngineeringOperations researchOperating systemMechanical engineeringArchaeologyHistoryNetwork Security and Intrusion DetectionInformation and Cyber SecurityAdvanced Malware Detection Techniques