Adversarials: Anti-AI Countermeasures

Author:

Kwik Jonathan

Publisher

T.M.C. Asser Press

Reference71 articles.

1. Amodei D et al. (2016) Concrete Problems in AI Safety. http://arxiv.org/abs/1606.06565

2. Athalye A et al. (2018) Synthesizing Robust Adversarial Examples. In: 6th International Conference on Learning Representations (ICLR 2018). OpenReview.net, Vancouver. https://openreview.net/forum?id=BJDH5M-AW. Accessed 3 August 2023

3. Barredo Arrieta A et al. (2020) Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI. Information Fusion 58:82–115. https://doi.org/10.1016/j.inffus.2019.12.012

4. Barreno M et al. (2010) The Security of Machine Learning. Machine Learning 81(2):121–148. https://doi.org/10.1007/s10994-010-5188-5

5. Biggio B et al. (2013) Evasion Attacks against Machine Learning at Test Time BT - Machine Learning and Knowledge Discovery in Databases. In: Blockeel H et al. (eds) Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2013 Prague, Czech Republic, September 23–27, 2013. Springer Berlin Heidelberg, Berlin, pp 387–402

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