Towards Resilient Artificial Intelligence: Survey and Research Issues
Oliver Eigner, Sebastian Eresheim, Peter Kieseberg, Lukas Daniel Klausner, Martin Pirker, Torsten Priebe, Simon Tjoa, Fiammetta Marulli, Francesco Mercaldo
Abstract
Artificial intelligence (AI) systems are becoming critical components of today’s IT landscapes. Their resilience against attacks and other environmental influences needs to be ensured just like for other IT assets. Considering the particular nature of AI, and machine learning (ML) in particular, this paper provides an overview of the emerging field of resilient AI and presents research issues the authors identify as potential future work.
Topics & Concepts
Resilience (materials science)Computer scienceField (mathematics)Work (physics)Artificial intelligenceData scienceApplications of artificial intelligenceManagement scienceEngineeringMechanical engineeringPhysicsPure mathematicsThermodynamicsMathematicsAdversarial Robustness in Machine LearningAnomaly Detection Techniques and ApplicationsNetwork Security and Intrusion Detection