Sfoglia per Autore
Explainability-based Debugging of Machine Learning for Vulnerability Discovery
2022-01-01 Sotgiu, Angelo; Pintor, Maura; Biggio, Battista
Industrial practitioners' mental models of adversarial machine learning
2022-01-01 Bieringer, L.; Grosse, K.; Backes, M.; Biggio, B.; Krombholz, K.
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.
Tessellation-Filtering ReLU Neural Networks
2022-01-01 Moser, Bernhard A.; Lewandowski, Michal; Kargaran, Somayeh; Zellinger, Werner; Biggio, Battista; Koutschan, Christoph
Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware
2022-01-01 Demetrio, L; Biggio, B; Roli, F
secml: Secure and explainable machine learning in Python
2022-01-01 Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Melis, Marco; Demontis, Ambra; Biggio, Battista
Towards learning trustworthily, automatically, and with guarantees on graphs: an overview
2022-01-01 Oneto, Luca; Navarin, Nicoló; Biggio, Battista; Errica, Federico; Micheli, Alessio; Scarselli, Franco; Bianchini, Monica; Demetrio, Luca; Bongini, Pietro; Tacchella, Armando; Sperduti, Alessandro
Explaining Machine Learning DGA Detectors from DNS Traffic Data
2022-01-01 Piras, Giorgio; Pintor, Maura; Demetrio, Luca; Biggio, Battista
Robust Machine Learning for Malware Detection over Time
2022-01-01 Angioni, Daniele; Demetrio, Luca; Pintor, Maura; Biggio, Battista
Practical Evaluation of Poisoning Attacks on Online Anomaly Detectors in Industrial Control Systems
2022-01-01 Kravchik, M.; Demetrio, L.; Biggio, B.; Shabtai, A.
FADER: Fast Adversarial Example Rejection
2022-01-01 Crecchi, Francesco; Melis, Marco; Sotgiu, Angelo; Bacciu, Davide; Biggio, Battista
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.
Backdoor smoothing: Demystifying backdoor attacks on deep neural networks
2022-01-01 Grosse, K; Lee, Ts; Biggio, B; Park, Y; Backes, M; Molloy, I
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
Empirical assessment of generating adversarial configurations for software product lines
2021-01-01 Temple, P.; Perrouin, G.; Acher, M.; Biggio, B.; Jezequel, J. -M.; Roli, F.
Poisoning Attacks on Algorithmic Fairness
2021-01-01 Solans, D.; Biggio, B.; Castillo, C.
Poisoning attacks on cyber attack detectors for industrial control systems
2021-01-01 Kravchik, Moshe; Biggio, Battista; Shabtai, Asaf
Complex Data: Learning Trustworthily, Automatically, and with Guarantees
2021-01-01 Oneto, L.; Navarin, N.; Biggio, B.; Errica, F.; Micheli, A.; Scarselli, F.; Bianchini, M.; Sperduti, A.
Fast minimum-norm adversarial attacks through adaptive norm constraints
2021-01-01 Pintor, Maura; Roli, Fabio; Brendel, Wieland; Biggio, Battista
Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware
2021-01-01 Demetrio, Luca; Biggio, Battista; Lagorio, Giovanni; Roli, Fabio; Armando, Alessandro
| Titolo | Data di pubblicazione | Autore(i) | Rivista | Editore |
|---|---|---|---|---|
| Explainability-based Debugging of Machine Learning for Vulnerability Discovery | 1-gen-2022 | Sotgiu, Angelo; Pintor, Maura; Biggio, Battista | - | ACM, Association for Computing Machinery |
| Industrial practitioners' mental models of adversarial machine learning | 1-gen-2022 | Bieringer, L.; Grosse, K.; Backes, M.; Biggio, B.; Krombholz, K. | - | USENIX Association |
| 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 | - |
| Tessellation-Filtering ReLU Neural Networks | 1-gen-2022 | Moser, Bernhard A.; Lewandowski, Michal; Kargaran, Somayeh; Zellinger, Werner; Biggio, Battista; Koutschan, Christoph | - | - |
| Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware | 1-gen-2022 | Demetrio, L; Biggio, B; Roli, F | IEEE SECURITY & PRIVACY | - |
| secml: Secure and explainable machine learning in Python | 1-gen-2022 | Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Melis, Marco; Demontis, Ambra; Biggio, Battista | SOFTWAREX | - |
| Towards learning trustworthily, automatically, and with guarantees on graphs: an overview | 1-gen-2022 | Oneto, Luca; Navarin, Nicoló; Biggio, Battista; Errica, Federico; Micheli, Alessio; Scarselli, Franco; Bianchini, Monica; Demetrio, Luca; Bongini, Pietro; Tacchella, Armando; Sperduti, Alessandro | NEUROCOMPUTING | - |
| Explaining Machine Learning DGA Detectors from DNS Traffic Data | 1-gen-2022 | Piras, Giorgio; Pintor, Maura; Demetrio, Luca; Biggio, Battista | - | - |
| Robust Machine Learning for Malware Detection over Time | 1-gen-2022 | Angioni, Daniele; Demetrio, Luca; Pintor, Maura; Biggio, Battista | - | - |
| Practical Evaluation of Poisoning Attacks on Online Anomaly Detectors in Industrial Control Systems | 1-gen-2022 | Kravchik, M.; Demetrio, L.; Biggio, B.; Shabtai, A. | COMPUTERS & SECURITY | - |
| FADER: Fast Adversarial Example Rejection | 1-gen-2022 | Crecchi, Francesco; Melis, Marco; Sotgiu, Angelo; Bacciu, Davide; Biggio, Battista | NEUROCOMPUTING | - |
| 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 | - |
| Backdoor smoothing: Demystifying backdoor attacks on deep neural networks | 1-gen-2022 | Grosse, K; Lee, Ts; Biggio, B; Park, Y; Backes, M; Molloy, I | COMPUTERS & SECURITY | - |
| 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 | - | Neural information processing systems foundation |
| Empirical assessment of generating adversarial configurations for software product lines | 1-gen-2021 | Temple, P.; Perrouin, G.; Acher, M.; Biggio, B.; Jezequel, J. -M.; Roli, F. | EMPIRICAL SOFTWARE ENGINEERING | - |
| Poisoning Attacks on Algorithmic Fairness | 1-gen-2021 | Solans, D.; Biggio, B.; Castillo, C. | - | Springer Science and Business Media Deutschland GmbH |
| Poisoning attacks on cyber attack detectors for industrial control systems | 1-gen-2021 | Kravchik, Moshe; Biggio, Battista; Shabtai, Asaf | - | - |
| Complex Data: Learning Trustworthily, Automatically, and with Guarantees | 1-gen-2021 | Oneto, L.; Navarin, N.; Biggio, B.; Errica, F.; Micheli, A.; Scarselli, F.; Bianchini, M.; Sperduti, A. | - | - |
| Fast minimum-norm adversarial attacks through adaptive norm constraints | 1-gen-2021 | Pintor, Maura; Roli, Fabio; Brendel, Wieland; Biggio, Battista | - | - |
| Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware | 1-gen-2021 | Demetrio, Luca; Biggio, Battista; Lagorio, Giovanni; Roli, Fabio; Armando, Alessandro | IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY | - |
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