Lights Toward Adversarial Machine Learning: The Achilles Heel of Artificial Intelligence
Luca Pajola, Mauro Conti · IEEE Intelligent Systems · 2024
Artificial intelligence (AI)-based technologies are starting to be adopted in the industrial world in many different contexts and sectors, from health care to the automotive, from agriculture to the industrial. As such applications operate in sensitive contexts, it is natural to question: Are they cyber-secure? Can attackers exploit AI applications for their attack? In this work, we discuss the Achilles heel of artificial intelligence: the “adversarial machine learning.” From a cybersecurity practitioner’s point of view, we discuss threats related to AI applications that include each component involved in the AI process, from the operative systems and libraries utilized to deploy the AI application, to the actual AI lifecycle.