DEMONTIS, AMBRA
DEMONTIS, AMBRA
DIPARTIMENTO DI INGEGNERIA ELETTRICA ED ELETTRONICA
A Hybrid Training-Time and Run-Time Defense Against Adversarial Attacks in Modulation Classification
2022-01-01 Zhang, L; Lambotharan, S; Zheng, G; Liao, Gs; Demontis, A; Roli, F
Adversarial Detection of Flash Malware: Limitations and Open Issues
2020-01-01 Maiorca, D.; Demontis, A.; Biggio, B.; Roli, F.; Giacinto, G.
Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables
2018-01-01 Kolosnjaji, Bojan; Demontis, Ambra; Biggio, Battista; Maiorca, Davide; Giacinto, Giorgio; Eckert, Claudia; Roli, Fabio
AI Security and Safety: The PRALab Research Experience
2023-01-01 Demontis, Ambra; Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Angioni, Daniele; Piras, Giorgio; Gupta, Srishti; Biggio, Battista; Roli, Fabio
Cybersecurity and AI: The PRALab Research Experience
2023-01-01 Pintor, Maura; Orru, Giulia; Maiorca, Davide; Demontis, Ambra; Demetrio, Luca; Marcialis, GIAN LUCA; Biggio, Battista; Roli, Fabio
Deep neural rejection against adversarial examples
2020-01-01 Sotgiu, Angelo; Demontis, Ambra; Melis, Marco; Biggio, Battista; Fumera, Giorgio; Feng, Xiaoyi; Roli, Fabio
Detecting Attacks Against Deep Reinforcement Learning for Autonomous Driving
2023-01-01 Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Lin, HSIAO-YING; Fang, Chengfang; Demontis, Ambra; Biggio, Battista
Do gradient-based explanations tell anything about adversarial robustness to android malware?
2022-01-01 Melis, M.; Scalas, M.; Demontis, A.; Maiorca, D.; Biggio, B.; Giacinto, G.; Roli, F.
Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers
2022-01-01 Melacci, S.; Ciravegna, G.; Sotgiu, A.; Demontis, A.; Biggio, B.; Gori, M.; Roli, F.
ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches
2023-01-01 Pintor, Maura; Angioni, Daniele; Sotgiu, Angelo; Demetrio, Luca; Demontis, Ambra; Biggio, Battista; Roli, Fabio
Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization
2023-01-01 Floris, Giuseppe; Mura, Raffaele; Scionis, Luca; Piras, Giorgio; Pintor, Maura; Demontis, Ambra; Biggio, Battista
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples
2022-01-01 Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Demontis, Ambra; Carlini, Nicholas; Biggio, Battista; Roli, Fabio
Infinity-norm support vector machines against adversarial label contamination
2017-01-01 Demontis, Ambra; Biggio, Battista; Fumera, Giorgio; Giacinto, Giorgio; Roli, Fabio
Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid
2018-01-01 Melis, Marco; Demontis, Ambra; Biggio, Battista; Brown, Gavin; Fumera, Giorgio; Roli, Fabio
Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training
2023-01-01 Lazzaro, Dario; Cinà, Antonio Emanuele; Pintor, Maura; Demontis, Ambra; Biggio, Battista; Roli, Fabio; Pelillo, Marcello
On security and sparsity of linear classifiers for adversarial settings
2016-01-01 Demontis, Ambra; Russu, Paolo; Biggio, Battista; Fumera, Giorgio; Roli, Fabio
Samples on Thin Ice: Re-evaluating Adversarial Pruning of Neural Networks
2023-01-01 Piras, Giorgio; Pintor, Maura; Demontis, Ambra; Biggio, Battista
secml: Secure and explainable machine learning in Python
2022-01-01 Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Melis, Marco; Demontis, Ambra; Biggio, Battista
Secure Kernel Machines against Evasion Attacks
2016-01-01 Russu, Paolo; Demontis, Ambra; Biggio, Battista; Fumera, Giorgio; Roli, Fabio
Securing Machine Learning against Adversarial Attacks
2018-03-26
| Titolo | Data di pubblicazione | Autore(i) | Rivista | Editore |
|---|---|---|---|---|
| A Hybrid Training-Time and Run-Time Defense Against Adversarial Attacks in Modulation Classification | 1-gen-2022 | Zhang, L; Lambotharan, S; Zheng, G; Liao, Gs; Demontis, A; Roli, F | IEEE WIRELESS COMMUNICATIONS LETTERS | - |
| Adversarial Detection of Flash Malware: Limitations and Open Issues | 1-gen-2020 | Maiorca, D.; Demontis, A.; Biggio, B.; Roli, F.; Giacinto, G. | COMPUTERS & SECURITY | - |
| Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables | 1-gen-2018 | Kolosnjaji, Bojan; Demontis, Ambra; Biggio, Battista; Maiorca, Davide; Giacinto, Giorgio; Eckert, Claudia; Roli, Fabio | - | IEEE (Institute of Electrical and Electronics Engineers) |
| AI Security and Safety: The PRALab Research Experience | 1-gen-2023 | Demontis, Ambra; Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Angioni, Daniele; Piras, Giorgio; Gupta, Srishti; Biggio, Battista; Roli, Fabio | - | CEUR-WS Team, Redaktion Sun SITE |
| Cybersecurity and AI: The PRALab Research Experience | 1-gen-2023 | Pintor, Maura; Orru, Giulia; Maiorca, Davide; Demontis, Ambra; Demetrio, Luca; Marcialis, GIAN LUCA; Biggio, Battista; Roli, Fabio | - | CEUR-WS Team, Redaktion Sun SITE |
| Deep neural rejection against adversarial examples | 1-gen-2020 | Sotgiu, Angelo; Demontis, Ambra; Melis, Marco; Biggio, Battista; Fumera, Giorgio; Feng, Xiaoyi; Roli, Fabio | EURASIP JOURNAL ON MULTIMEDIA AND INFORMATION SECURITY | - |
| Detecting Attacks Against Deep Reinforcement Learning for Autonomous Driving | 1-gen-2023 | Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Lin, HSIAO-YING; Fang, Chengfang; Demontis, Ambra; Biggio, Battista | - | - |
| Do gradient-based explanations tell anything about adversarial robustness to android malware? | 1-gen-2022 | Melis, M.; Scalas, M.; Demontis, A.; Maiorca, D.; Biggio, B.; Giacinto, G.; Roli, F. | INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS | - |
| Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers | 1-gen-2022 | Melacci, S.; Ciravegna, G.; Sotgiu, A.; Demontis, A.; Biggio, B.; Gori, M.; Roli, F. | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | - |
| ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches | 1-gen-2023 | Pintor, Maura; Angioni, Daniele; Sotgiu, Angelo; Demetrio, Luca; Demontis, Ambra; Biggio, Battista; Roli, Fabio | PATTERN RECOGNITION | - |
| Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization | 1-gen-2023 | Floris, Giuseppe; Mura, Raffaele; Scionis, Luca; Piras, Giorgio; Pintor, Maura; Demontis, Ambra; Biggio, Battista | - | Ciaco - i6doc.com |
| Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples | 1-gen-2022 | Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Demontis, Ambra; Carlini, Nicholas; Biggio, Battista; Roli, Fabio | - | - |
| Infinity-norm support vector machines against adversarial label contamination | 1-gen-2017 | Demontis, Ambra; Biggio, Battista; Fumera, Giorgio; Giacinto, Giorgio; Roli, Fabio | - | CEUR-WS |
| Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid | 1-gen-2018 | Melis, Marco; Demontis, Ambra; Biggio, Battista; Brown, Gavin; Fumera, Giorgio; Roli, Fabio | - | IEEE (Institute of Electrical and Electronics Engineers) |
| Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training | 1-gen-2023 | Lazzaro, Dario; Cinà, Antonio Emanuele; Pintor, Maura; Demontis, Ambra; Biggio, Battista; Roli, Fabio; Pelillo, Marcello | - | - |
| On security and sparsity of linear classifiers for adversarial settings | 1-gen-2016 | Demontis, Ambra; Russu, Paolo; Biggio, Battista; Fumera, Giorgio; Roli, Fabio | - | Springer |
| Samples on Thin Ice: Re-evaluating Adversarial Pruning of Neural Networks | 1-gen-2023 | Piras, Giorgio; Pintor, Maura; Demontis, Ambra; Biggio, Battista | - | - |
| secml: Secure and explainable machine learning in Python | 1-gen-2022 | Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Melis, Marco; Demontis, Ambra; Biggio, Battista | SOFTWAREX | - |
| Secure Kernel Machines against Evasion Attacks | 1-gen-2016 | Russu, Paolo; Demontis, Ambra; Biggio, Battista; Fumera, Giorgio; Roli, Fabio | - | Association for Computing Machinery |
| Securing Machine Learning against Adversarial Attacks | 26-mar-2018 | - | - | Università degli Studi di Cagliari |