Journal Publications

  • Apruzzese G, Colajanni M., Ferretti L, Guido, A. and Marchetti M (2018) May. On the effectiveness of machine and deep learning for cyber security. In 2018 10th International Conference on Cyber Conflict (CyCon). IEEE.
  • Anderson H.S, Woodbridge J, and Filar B (2016) October. DeepDGA: Adversarially-tuned domain generation and detection. In Proceedings of the 2016 ACM Workshop on Artificial Intelligence and Security (pp. 13-21). ACM.
  • Arjovsky, M., Chintala, S. and Bottou, L (2017) Wasserstein gan. arXiv preprint arXiv:1701.07875.
  • Goodfellow I J, Shlens J and Szegedy C (2014) Explaining and harnessing adversarial examples arXiv preprint arXiv:1412.6572.
  • Hayes, J., Melis, L., Danezis, G. and De Cristofaro, E., 2019. LOGAN: Membership inference attacks against generative models. Proceedings on Privacy Enhancing Technologies, 2019(1), pp.133-152.
  • Hinton G.E and Sejnowski T.J (1986) Learning and relearning in Boltzmann machines. Parallel distributed processing: Explorations in the microstructure of cognition, 1, pp.282-317.
  • Malhotra Y (2018) Machine Intelligence: AI, Machine Learning, Deep Learning & Generative Adversarial Networks: Model Risk Management in Operationalizing Machine Learning for Algorithm Deployment.
  • Salimans T, Goodfellow I, Zaremba W, Cheung V, Radford A and Chen X (2016) Improved techniques for training gans. In Advances in Neural Information Processing Systems, pages 2226–2234.