Towards Resilient Artificial Intelligence: Survey and Research Issues
| Autor: | Martin Pirker, Peter Kieseberg, Lukas Daniel Klausner, Sebastian Eresheim, Francesco Mercaldo, Torsten Priebe, Fiammetta Marulli, Oliver Eigner, Simon Tjoa |
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| Přispěvatelé: | O. Eigner, S. Eresheim, P. Kieseberg, L. Klausner, M. Pirker, T. Priebe, S.Tjoa, F. Marulli, F. Mercaldo, Institute of Electrical and Electronics Engineers Inc., Eigner, O., Eresheim, S., Kieseberg, P., Klausner, L. D., Pirker, M., Priebe, T., Tjoa, S., Marulli, F., Mercaldo, F. |
| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Machine Learning Computer Science - Cryptography and Security Computer Science - Artificial Intelligence business.industry Computer science It assets GeneralLiterature_MISCELLANEOUS Field (computer science) Machine Learning (cs.LG) Computer Science - Computers and Society Artificial Intelligence (cs.AI) Work (electrical) Computers and Society (cs.CY) Artificial intelligence business Resilience (network) Cryptography and Security (cs.CR) |
| Zdroj: | 2021 IEEE International Conference on Cyber Security and Resilience (CSR). |
| DOI: | 10.1109/csr51186.2021.9527986 |
| Popis: | 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. Comment: 7 pages, 1 figure |
| Databáze: | OpenAIRE |
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