Open Access
ITM Web Conf.
Volume 59, 2024
II International Workshop “Hybrid Methods of Modeling and Optimization in Complex Systems” (HMMOCS-II 2023)
Article Number 04011
Number of page(s) 9
Section Adaptive Intelligence: Exploring Learning in Evolutionary Algorithms and Neural Networks
Published online 25 January 2024
  1. J. Kos, I. Fischer, D. Song, Adversarial examples for generative models, in Proceedings of the IEEE Security and Privacy Workshops (2018) [Google Scholar]
  2. N. Papernot, P. McDaniel, I. Goodfellow, S. Jha, Z.B. Celik, A. Swami, Practical blackbox attacks against machine learning, in Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security (2017) [Google Scholar]
  3. Z. Wang, M. Song, Z. Zhang, Y. Song, Q. Wang, H. Qi, Beyond Inferring ClassRepresentatives: User-Level Privacy Leakage From Federated Learning, in Proceedings IEEE Int. Conf. on Computer Communications (2019) [Google Scholar]
  4. A. Alotaibi, M. Rassam, Future Internet 15(2) (2023) [Google Scholar]
  5. A. Aldweesh, A. Derhab, A.Z. Emam, Knowledge-Based Systems 189 (2020) [Google Scholar]
  6. Q. Dong, Leakage Prediction in Machine Learning Models When Using Data from Sports Wearable Sensors, Computational Intelligence and Neuroscience (2022) [Google Scholar]
  7. A. Salem, Y. Zhang, M. Humbert, P. Berrang, M. Fritz, M. Backes, Ml-leaks: Model and data independent membership inference attacks and defenses on machine learning models arXiv preprint arXiv:1806.01246 (2019) [Google Scholar]
  8. U. Noor, Z. Anwar, A.W. Malik, S. Khan, S. Saleem, Future Generation Computer Systems 95 (2019) [Google Scholar]
  9. L. Song, R. Shokri, P. Mittal, Privacy risks of securing machine learning models against adversarial examples, in Proceedings ACM SIGSAC Conference on Computer and Communications Security, 2019 [Google Scholar]
  10. O. Ibitoye, R. Abou-Khamis, M.E. Shehaby, A. Matrawy, M.O. Shafiq, The Threat of Adversarial Attacks on Machine Learning in Network Security - A Survey arXiv preprint arXiv:1911.0262 (2019) [Google Scholar]

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