| Towards poisoning of deep learning algorithms with back-gradient optimization L Muñoz-González, B Biggio, A Demontis, A Paudice, V Wongrassamee, ... Proceedings of the 10th ACM workshop on artificial intelligence and security …, 2017 | 597 | 2017 |
| Automated dynamic analysis of ransomware: Benefits, limitations and use for detection D Sgandurra, L Muñoz-González, R Mohsen, EC Lupu arXiv preprint arXiv:1609.03020, 2016 | 340 | 2016 |
| Label Sanitization against Label Flipping Poisoning Attacks A Paudice, L Muñoz-González, EC Lupu arXiv preprint: arXiv:1803.00992, 2018 | 151 | 2018 |
| Detection of Adversarial Training Examples in Poisoning Attacks through Anomaly Detection A Paudice, L Muñoz-González, A Gyorgy, EC Lupu arXiv preprint: arXiv:1802.03041, 2018 | 150 | 2018 |
| Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging L Muñoz-González, KT Co, EC Lupu arXiv preprint arXiv:1902.05083, 2019 | 136* | 2019 |
| Exact inference techniques for the analysis of Bayesian attack graphs L Muñoz-González, D Sgandurra, M Barrère, EC Lupu IEEE Transactions on Dependable and Secure Computing 16 (2), 231-244, 2017 | 96 | 2017 |
| Poisoning attacks with generative adversarial nets L Muñoz-González, B Pfitzner, M Russo, J Carnerero-Cano, EC Lupu arXiv preprint arXiv:1906.07773, 2019 | 69 | 2019 |
| Efficient Attack Graph Analysis through Approximate Inference L Muñoz-González, D Sgandurra, A Paudice, EC Lupu ACM Transactions on Privacy and Security (TOPS) 20 (3), 10, 2017 | 57 | 2017 |
| Procedural noise adversarial examples for black-box attacks on deep convolutional networks KT Co, L Muñoz-González, S de Maupeou, EC Lupu Proceedings of the 2019 ACM SIGSAC conference on computer and communications …, 2019 | 46 | 2019 |
| Robust aggregation for adaptive privacy preserving federated learning in healthcare M Grama, M Musat, L Muñoz-González, J Passerat-Palmbach, D Rueckert, ... arXiv preprint arXiv:2009.08294, 2020 | 39 | 2020 |
| Non-IID data re-balancing at IoT edge with peer-to-peer federated learning for anomaly detection H Wang, L Muñoz-González, D Eklund, S Raza Proceedings of the 14th ACM Conference on Security and Privacy in Wireless …, 2021 | 29 | 2021 |
| The security of machine learning systems L Muñoz-González, EC Lupu AI in Cybersecurity, 47-79, 2019 | 26 | 2019 |
| Don't fool me!: detection, characterisation and diagnosis of spoofed and masked events in wireless sensor networks VP Illiano, L Muñoz-González, EC Lupu IEEE Transactions on Dependable and Secure Computing 14 (3), 279-293, 2016 | 25 | 2016 |
| Heteroscedastic Gaussian process regression using expectation propagation L Muñoz-González, M Lázaro-Gredilla, AR Figueiras-Vidal 2011 IEEE International Workshop on Machine Learning for Signal Processing, 1-6, 2011 | 23 | 2011 |
| Realizable Universal Adversarial Perturbations for Malware R Labaca-Castro, L Muñoz-González, F Pendlebury, GD Rodosek, ... arXiv preprint arXiv:2102.06747, 2021 | 19* | 2021 |
| Shadow-catcher: Looking into shadows to detect ghost objects in autonomous vehicle 3d sensing Z Hau, S Demetriou, L Muñoz-González, EC Lupu Computer Security–ESORICS 2021: 26th European Symposium on Research in …, 2021 | 17* | 2021 |
| Bayesian attack graphs for security risk assessment L Munoz Gonzalez, E Lupu | 17 | 2016 |
| Divisive Gaussian processes for nonstationary regression L Muñoz-González, M Lázaro-Gredilla, AR Figueiras-Vidal IEEE Transactions On Neural Networks and Learning Systems 25 (11), 1991-2003, 2014 | 17 | 2014 |
| Approaches to enhancing cyber resilience: Report of the north atlantic treaty organization (NATO) workshop IST-153 A Kott, B Blakely, D Henshel, G Wehner, J Rowell, N Evans, ... arXiv preprint arXiv:1804.07651, 2018 | 16 | 2018 |
| Laplace approximation for divisive Gaussian processes for nonstationary regression L Munoz-Gonzalez, M Lazaro-Gredilla, AR Figueiras-Vidal IEEE transactions on pattern analysis and machine intelligence 38 (3), 618-624, 2015 | 16 | 2015 |
Emil LupuProfessor of Computer SystemsVerified email at imperial.ac.uk
