An overview of my scientific publications.


  1. Improving the robustness of deep neural networks to adversarial perturbations
    Jonathan Peck
    Ghent University, 2023


  1. Distilling Deep RL Models Into Interpretable Neuro-Fuzzy Systems
    Arne Gevaert, Jonathan Peck, and Yvan Saeys


  1. Inline Detection of DGA Domains Using Side Information
    Raaghavi Sivaguru, Jonathan Peck, Femi Olumofin, and 2 more authors
    IEEE Access, 2020
  2. Calibrated Multi-probabilistic Prediction as a Defense Against Adversarial Attacks
    Jonathan Peck, Bart Goossens, and Yvan Saeys
    In Artificial Intelligence and Machine Learning, 2020
  3. Regional image perturbation reduces L_p norms of adversarial examples while maintaining model-to-model transferability
    Utku Özbulak, Jonathan Peck, Wesley De Neve, and 3 more authors
    In the 37th International Conference on Machine Learning (ICML 2020), Proceedings, 2020


  1. CharBot: A Simple and Effective Method for Evading DGA Classifiers
    Jonathan Peck, Claire Nie, Raaghavi Sivaguru, and 5 more authors
    IEEE Access, 2019
  2. Hardening DGA Classifiers Utilizing IVAP
    Charles Grumer, Jonathan Peck, Femi Olumofin, and 2 more authors
    In 2019 IEEE International Conference on Big Data (Big Data), 2019
  3. Detecting adversarial examples with inductive Venn-ABERS predictors
    Jonathan Peck, Bart Goossens, and Yvan Saeys
    In Proceedings of the 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2019), 2019


  1. Lower bounds on the robustness to adversarial perturbations
    Jonathan Peck, Joris Roels, Bart Goossens, and 1 more author
    In Advances in Neural Information Processing Systems, 2017