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Antonio Emanuele Cinà
Antonio Emanuele Cinà
Other namesAntonio Cinà
Assistant Professor @ University of Genoa
Verified email at unige.it - Homepage
Title
Cited by
Cited by
Year
Wild patterns reloaded: A survey of machine learning security against training data poisoning
AE Cinà, K Grosse, A Demontis, S Vascon, W Zellinger, BA Moser, ...
ACM Computing Surveys 55 (13s), 1-39, 2023
812023
A black-box adversarial attack for poisoning clustering
AE Cinà, A Torcinovich, M Pelillo
Pattern Recognition 122, 108306, 2022
442022
Machine learning security against data poisoning: Are we there yet?
AE Cinà, K Grosse, A Demontis, B Biggio, F Roli, M Pelillo
IEEE Computer 57 (Issue 3), 26 - 34, 2024
332024
Energy-latency attacks via sponge poisoning
AE Cinà, A Demontis, B Biggio, F Roli, M Pelillo
arXiv preprint arXiv:2203.08147, 2022
202022
The hammer and the nut: Is bilevel optimization really needed to poison linear classifiers?
AE Cinà, S Vascon, A Demontis, B Biggio, F Roli, M Pelillo
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
152021
Backdoor learning curves: Explaining backdoor poisoning beyond influence functions
AE Cinà, K Grosse, S Vascon, A Demontis, B Biggio, F Roli, M Pelillo
arXiv preprint arXiv:2106.07214, 2021
152021
Minimizing energy consumption of deep learning models by energy-aware training
D Lazzaro, AE Cinà, M Pintor, A Demontis, B Biggio, F Roli, M Pelillo
International Conference on Image Analysis and Processing, 515-526, 2023
62023
Conning the Crypto Conman: End-to-End Analysis of Cryptocurrency-based Technical Support Scams
B Acharya, M Saad, AE Cinà, L Schönherr, HD Nguyen, A Oest, ...
IEEE Symposium on Security and Privacy (S&P), 156-156, 2024
32024
On the Limitations of Model Stealing with Uncertainty Quantification Models
D Pape, S Däubener, T Eisenhofer, AE Cinà, L Schönherr
European Symposium on Artificial Neural Networks, Computational Intelligence …, 2023
22023
Security of Machine Learning (Dagstuhl Seminar 22281)
B Biggio, N Carlini, P Laskov, K Rieck, AE Cinà
Dagstuhl Reports 12 (7), 41--61, 2023
22023
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
AE Cinà, J Rony, M Pintor, L Demetrio, A Demontis, B Biggio, IB Ayed, ...
arXiv preprint arXiv:2404.19460, 2024
12024
Hardening RGB-D object recognition systems against adversarial patch attacks
Y Zheng, L Demetrio, AE Cinà, X Feng, Z Xia, X Jiang, A Demontis, ...
Information Sciences 651, 119701, 2023
12023
Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis
Z Chen, L Demetrio, S Gupta, X Feng, Z Xia, AE Cinà, M Pintor, L Oneto, ...
arXiv preprint arXiv:2406.10090, 2024
2024
-zero: Gradient-based Optimization of -norm Adversarial Examples
AE Cinà, F Villani, M Pintor, L Schönherr, B Biggio, M Pelillo
arXiv preprint arXiv:2402.01879, 2024
2024
Vector Flows and the Capacity of a Discrete Memoryless Channel
G Beretta, G Chiarot, AE Cinà, M Pelillo
arXiv preprint arXiv:2312.16472, 2023
2023
Vulnerability of Machine Learning: A Study on Poisoning Attacks
AE Cina
Università Ca'Foscari Venezia, 2023
2023
On the Robustness of Clustering Algorithms to Adversarial Attacks
AE Cina
Università Ca'Foscari Venezia, 2019
2019
The Imitation Game: Exploring Brand Impersonation Attacks on Social Media Platforms
B Acharya, D Lazzaro, E López-Morales, A Oest, M Saad, AE Cinà, ...
This is the Author’s preprint manuscript version of the following contribution
AE Cinà, K Grosse, A Demontis, S Vascon, W Zellinger, BA Moser
3.3 Where ML Security Is Broken and How to Fix It
AE Cinà, M Pintor
Security of Machine Learning, 47, 0
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