Maura Pintor
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Why do adversarial attacks transfer? explaining transferability of evasion and poisoning attacks
A Demontis, M Melis, M Pintor, M Jagielski, B Biggio, A Oprea, ...
28th USENIX security symposium (USENIX security 19), 321-338, 2019
The threat of offensive ai to organizations
Y Mirsky, A Demontis, J Kotak, R Shankar, D Gelei, L Yang, X Zhang, ...
Computers & Security 124, 103006, 2023
Fast minimum-norm adversarial attacks through adaptive norm constraints
M Pintor, F Roli, W Brendel, B Biggio
Advances in Neural Information Processing Systems 34, 20052-20062, 2021
secml: A python library for secure and explainable machine learning
M Melis, A Demontis, M Pintor, A Sotgiu, B Biggio
arXiv preprint arXiv:1912.10013 6, 2019
ImageNet-Patch: A dataset for benchmarking machine learning robustness against adversarial patches
M Pintor, D Angioni, A Sotgiu, L Demetrio, A Demontis, B Biggio, F Roli
Pattern Recognition 134, 109064, 2023
Indicators of attack failure: Debugging and improving optimization of adversarial examples
M Pintor, L Demetrio, A Sotgiu, A Demontis, N Carlini, B Biggio, F Roli
Advances in Neural Information Processing Systems 35, 23063-23076, 2022
Why adversarial reprogramming works, when it fails, and how to tell the difference
Y Zheng, X Feng, Z Xia, X Jiang, A Demontis, M Pintor, B Biggio, F Roli
Information Sciences 632, 130-143, 2023
ALOHA: an architectural-aware framework for deep learning at the edge
P Meloni, D Loi, G Deriu, AD Pimentel, D Sapra, B Moser, N Shepeleva, ...
Proceedings of the workshop on INTelligent embedded systems architectures …, 2018
Be right Beach: A social IoT system for sustainable tourism based on beach overcrowding avoidance
R Girau, E Ferrara, M Pintor, M Sole, D Giusto
2018 IEEE International Conference on Internet of Things (iThings) and IEEE …, 2018
Optimization and deployment of CNNs at the edge: the ALOHA experience
P Meloni, D Loi, P Busia, G Deriu, AD Pimentel, D Sapra, T Stefanov, ...
Proceedings of the 16th ACM international conference on computing frontiers …, 2019
Explainability-based debugging of machine learning for vulnerability discovery
A Sotgiu, M Pintor, B Biggio
Proceedings of the 17th International Conference on Availability …, 2022
Detecting anomalies from video-sequences: a novel descriptor
G Orru, D Ghiani, M Pintor, GL Marcialis, F Roli
2020 25th International Conference on Pattern Recognition (ICPR), 4642-4649, 2021
Minimizing energy consumption of deep learning models by energy-aware training
D Lazzaro, AE Ciną, M Pintor, A Demontis, B Biggio, F Roli, M Pelillo
International Conference on Image Analysis and Processing, 515-526, 2023
Explaining machine learning DGA detectors from DNS traffic data
G Piras, M Pintor, L Demetrio, B Biggio
Evaluating adversarial attacks on imagenet: a reality check on misclassification classes
U Ozbulak, M Pintor, A Van Messem, W De Neve
arXiv preprint arXiv:2111.11056, 2021
Raze to the ground: Query-efficient adversarial html attacks on machine-learning phishing webpage detectors
B Montaruli, L Demetrio, M Pintor, L Compagna, D Balzarotti, B Biggio
Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security …, 2023
A survey on reinforcement learning security with application to autonomous driving
A Demontis, M Pintor, L Demetrio, K Grosse, HY Lin, C Fang, B Biggio, ...
arXiv preprint arXiv:2212.06123, 2022
Secml: Secure and Explainable Machine Learning in Python
M Melis, A Demontis, M Pintor, A Sotgiu, L Demetrio, B Biggio
Available at SSRN 4003262, 2022
Slope: A First-order Approach for Measuring Gradient Obfuscation
M Pintor, L Demetrio, G Manca, B Biggio, F Roli
ESANN 2021 - European Symposium on Artificial Neural Networks, Computational …, 2021
Rethinking data augmentation for adversarial robustness
H Eghbal-zadeh, W Zellinger, M Pintor, K Grosse, K Koutini, BA Moser, ...
Information Sciences 654, 119838, 2024
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