mlsanityData to 14 Oct 2026

Towards Resilient Artificial Intelligence: Survey and Research Issues

arXiv 2109.08904 ↗First posted 18 Sep 2021cs.LG cs.AI cs.CRcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 20 of its 67 references that are in the map. First posted on arXiv 18 Sep 2021.

Builds on

20 of 67 references.

References · 20

  1. 2014Explaining and Harnessing Adversarial Examplescited by 7,364
  2. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
  3. 2017Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real Worldcited by 1,498
  4. 2019Solving Rubik's Cube with a Robot Handcited by 734
  5. 2019Local Model Poisoning Attacks to Byzantine-Robust Federated Learningcited by 493
  6. 2017CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learningcited by 461
  7. 2017Robust Adversarial Reinforcement Learningcited by 451
  8. 2017Adversarial Attacks on Neural Network Policiescited by 320
  9. 2020Do Adversarially Robust ImageNet Models Transfer Better?cited by 316
  10. 2020Data Poisoning Attacks Against Federated Learning Systemscited by 275
  11. 2019Adversarial Policies: Attacking Deep Reinforcement Learningcited by 214
  12. 2017Robust Deep Reinforcement Learning with Adversarial Attackscited by 154
8 more
  1. 2017Vulnerability of Deep Reinforcement Learning to Policy Induction Attackscited by 91
  2. 2020Secure and Robust Machine Learning for Healthcare: A Surveycited by 80
  3. 2018Data Poisoning Attack against Unsupervised Node Embedding Methodscited by 19
  4. 2021Trusted Artificial Intelligence: Towards Certification of Machine Learning Applicationscited by 13
  5. 2019CopyCAT: Taking Control of Neural Policies with Constant Attackscited by 12
  6. 2019Minimalistic Attacks: How Little it Takes to Fool a Deep Reinforcement Learning Policycited by 10
  7. 2020Adversarial Attacks on Optimization based Plannerscited by 8
  8. 2021"Part Man, Part Machine, All Cop": Automation in Policingcited by 3

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Cited by year

Citing papers per year: 2023: 1; 2024: 1.

2 papers.

  1. 2024Cooperative Resilience in Artificial Intelligence Multiagent Systemscited by 8
  2. 2023SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learningcited by 3