Università degli Studi di Cagliari
Battista Biggio
When Your AI Becomes a Target: AI Security Incidents and Best Practices
2024-01-01 Grosse, Kathrin; Bieringer, Lukas; Besold, Tarek R.; Biggio, Battista; Alahi, Alexandre
Rethinking data augmentation for adversarial robustness
2024-01-01 Eghbal-zadeh, Hamid; Zellinger, Werner; Pintor, Maura; Grosse, Kathrin; Koutini, Khaled; Moser, Bernhard A.; Biggio, Battista; Widmer, Gerhard
Machine Learning Security Against Data Poisoning: Are We There Yet?
2024-01-01 Cinà, Antonio Emanuele; Grosse, Kathrin; Demontis, Ambra; Biggio, Battista; Roli, Fabio; Pelillo, Marcello
Nebula: Self-Attention for Dynamic Malware Analysis
2024-01-01 Trizna, Dmitrijs; Demetrio, Luca; Biggio, Battista; Roli, Fabio
Toward Effective Traffic Sign Detection via Two-Stage Fusion Neural Networks
2024-01-01 Li, Zhishan; Chen, Hongxu; Biggio, Battista; He, Yifan; Cai, Haoran; Roli, Fabio; Xie, Lei
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
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
Stateful detection of adversarial reprogramming
2023-01-01 Zheng, Yang; Feng, Xiaoyi; Xia, Zhaoqiang; Jiang, Xiaoyue; Pintor, Maura; Demontis, Ambra; Biggio, Battista; Roli, Fabio
Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage Detectors
2023-01-01 Montaruli, Biagio; Demetrio, Luca; Pintor, Maura; Compagna, Luca; Balzarotti, Davide; Biggio, Battista
Phantom Sponges: Exploiting Non-Maximum Suppression to Attack Deep Object Detectors
2023-01-01 Shapira, Avishag; Zolfi, Alon; Demetrio, Luca; Biggio, Battista; Shabtai, Asaf
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
Machine Learning Security in Industry: A Quantitative Survey
2023-01-01 Grosse, Kathrin; Bieringer, Lukas; Besold, Tarek R.; Biggio, Battista; Krombholz, Katharina
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
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
Samples on Thin Ice: Re-evaluating Adversarial Pruning of Neural Networks
2023-01-01 Piras, Giorgio; Pintor, Maura; Demontis, Ambra; Biggio, Battista
The Threat of Offensive AI to Organizations
2023-01-01 Mirsky, Y.; Demontis, A.; Kotak, J.; Shankar, R.; Gelei, D.; Yang, L.; Zhang, X.; Pintor, M.; Lee, W.; Elovici, Y.; Biggio, B.
Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning
2023-01-01 Emanuele Cinà, Antonio; Grosse, Kathrin; Demontis, Ambra; Vascon, Sebastiano; Zellinger, Werner; Moser, Bernhard A.; Oprea, Alina; Biggio, Battista; Pelillo, Marcello; Roli, Fabio
Why adversarial reprogramming works, when it fails, and how to tell the difference
2023-01-01 Zheng, Yang; Feng, Xiaoyi; Xia, Zhaoqiang; Jiang, Xiaoyue; Demontis, Ambra; Pintor, Maura; Biggio, Battista; Roli, Fabio
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
Adversarial Attacks Against Uncertainty Quantification
2023-01-01 Ledda, Emanuele; Angioni, Daniele; Piras, Giorgio; Fumera, Giorgio; Biggio, Battista; Roli, Fabio
Hardening RGB-D object recognition systems against adversarial patch attacks
2023-01-01 Zheng, Yang; Demetrio, Luca; Cinà, Antonio Emanuele; Feng, Xiaoyi; Xia, Zhaoqiang; Jiang, Xiaoyue; Demontis, Ambra; Biggio, Battista; Roli, Fabio
Tessellation-Filtering ReLU Neural Networks
2022-01-01 Moser, Bernhard A.; Lewandowski, Michal; Kargaran, Somayeh; Zellinger, Werner; Biggio, Battista; Koutschan, Christoph
Industrial practitioners' mental models of adversarial machine learning
2022-01-01 Bieringer, L.; Grosse, K.; Backes, M.; Biggio, B.; Krombholz, K.
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.
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
Explainability-based Debugging of Machine Learning for Vulnerability Discovery
2022-01-01 Sotgiu, Angelo; Pintor, Maura; Biggio, Battista
Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware
2022-01-01 Demetrio, L; Biggio, B; Roli, F
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
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.
Robust Machine Learning for Malware Detection over Time
2022-01-01 Angioni, Daniele; Demetrio, Luca; Pintor, Maura; Biggio, Battista
Backdoor smoothing: Demystifying backdoor attacks on deep neural networks
2022-01-01 Grosse, K; Lee, Ts; Biggio, B; Park, Y; Backes, M; Molloy, I
FADER: Fast Adversarial Example Rejection
2022-01-01 Crecchi, Francesco; Melis, Marco; Sotgiu, Angelo; Bacciu, Davide; 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
Explaining Machine Learning DGA Detectors from DNS Traffic Data
2022-01-01 Piras, Giorgio; Pintor, Maura; Demetrio, Luca; 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.
Poisoning attacks on cyber attack detectors for industrial control systems
2021-01-01 Kravchik, Moshe; Biggio, Battista; Shabtai, Asaf
Slope: A First-order Approach for Measuring Gradient Obfuscation
2021-01-01 Pintor, M.; Demetrio, L.; Manca, G.; Biggio, B.; Roli, F.
Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection
2021-01-01 Demetrio, L.; Coull, S. E.; Biggio, B.; Lagorio, G.; Armando, A.; Roli, F.
Adversarial Machine Learning: Attacks From Laboratories to the Real World
2021-01-01 Lin, Hsiao-Ying; Biggio, Battista
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.
The hammer and the nut: is bilevel optimization really needed to poison linear classifiers?
2021-01-01 Cina, A. E.; Vascon, S.; Demontis, A.; Biggio, B.; Roli, F.; Pelillo, M.
Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware
2021-01-01 Demetrio, Luca; Biggio, Battista; Lagorio, Giovanni; Roli, Fabio; Armando, Alessandro
Fast minimum-norm adversarial attacks through adaptive norm constraints
2021-01-01 Pintor, Maura; Roli, Fabio; Brendel, Wieland; Biggio, Battista
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.
Task-Specific Automation in Deep Learning Processes
2021-01-01 Buchgeher, G.; Czech, G.; Ribeiro, A. S.; Kloihofer, W.; Meloni, P.; Busia, P.; Deriu, G.; Pintor, M.; Biggio, B.; Chesta, C.; Rinelli, L.; Solans, D.; Portela, M.
Poisoning Attacks on Algorithmic Fairness
2021-01-01 Solans, D.; Biggio, B.; Castillo, C.
Deep neural rejection against adversarial examples
2020-01-01 Sotgiu, Angelo; Demontis, Ambra; Melis, Marco; Biggio, Battista; Fumera, Giorgio; Feng, Xiaoyi; Roli, Fabio
Adversarial Detection of Flash Malware: Limitations and Open Issues
2020-01-01 Maiorca, D.; Demontis, A.; Biggio, B.; Roli, F.; Giacinto, G.
Explaining vulnerabilities of deep learning to adversarial malware binaries
2019-01-01 Demetrio, Luca; Biggio, Battista; Lagorio, Giovanni; Roli, Fabio; Armando, Alessandro
Deep Learning and Security Workshop 2019
2019-01-01 Rieck, K.; Biggio, B.; Vasiloglou, N.
| Titolo | Data di pubblicazione | Autore(i) | Rivista | Editore |
|---|---|---|---|---|
| When Your AI Becomes a Target: AI Security Incidents and Best Practices | 1-gen-2024 | Grosse, Kathrin; Bieringer, Lukas; Besold, Tarek R.; Biggio, Battista; Alahi, Alexandre | - | - |
| Rethinking data augmentation for adversarial robustness | 1-gen-2024 | Eghbal-zadeh, Hamid; Zellinger, Werner; Pintor, Maura; Grosse, Kathrin; Koutini, Khaled; Moser, Bernhard A.; Biggio, Battista; Widmer, Gerhard | INFORMATION SCIENCES | - |
| Machine Learning Security Against Data Poisoning: Are We There Yet? | 1-gen-2024 | Cinà, Antonio Emanuele; Grosse, Kathrin; Demontis, Ambra; Biggio, Battista; Roli, Fabio; Pelillo, Marcello | COMPUTER | - |
| Nebula: Self-Attention for Dynamic Malware Analysis | 1-gen-2024 | Trizna, Dmitrijs; Demetrio, Luca; Biggio, Battista; Roli, Fabio | IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY | - |
| Toward Effective Traffic Sign Detection via Two-Stage Fusion Neural Networks | 1-gen-2024 | Li, Zhishan; Chen, Hongxu; Biggio, Battista; He, Yifan; Cai, Haoran; Roli, Fabio; Xie, Lei | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | - |
| 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 |
| 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 |
| Stateful detection of adversarial reprogramming | 1-gen-2023 | Zheng, Yang; Feng, Xiaoyi; Xia, Zhaoqiang; Jiang, Xiaoyue; Pintor, Maura; Demontis, Ambra; Biggio, Battista; Roli, Fabio | INFORMATION SCIENCES | - |
| Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage Detectors | 1-gen-2023 | Montaruli, Biagio; Demetrio, Luca; Pintor, Maura; Compagna, Luca; Balzarotti, Davide; Biggio, Battista | - | ASSOC COMPUTING MACHINERY |
| Phantom Sponges: Exploiting Non-Maximum Suppression to Attack Deep Object Detectors | 1-gen-2023 | Shapira, Avishag; Zolfi, Alon; Demetrio, Luca; Biggio, Battista; Shabtai, Asaf | - | IEEE |
| 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 | - | - |
| Machine Learning Security in Industry: A Quantitative Survey | 1-gen-2023 | Grosse, Kathrin; Bieringer, Lukas; Besold, Tarek R.; Biggio, Battista; Krombholz, Katharina | IEEE TRANSACTIONS ON INFORMATION FORENSICS AND 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 | - | - |
| 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 |
| Samples on Thin Ice: Re-evaluating Adversarial Pruning of Neural Networks | 1-gen-2023 | Piras, Giorgio; Pintor, Maura; Demontis, Ambra; Biggio, Battista | - | - |
| The Threat of Offensive AI to Organizations | 1-gen-2023 | Mirsky, Y.; Demontis, A.; Kotak, J.; Shankar, R.; Gelei, D.; Yang, L.; Zhang, X.; Pintor, M.; Lee, W.; Elovici, Y.; Biggio, B. | COMPUTERS & SECURITY | - |
| Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning | 1-gen-2023 | Emanuele Cinà, Antonio; Grosse, Kathrin; Demontis, Ambra; Vascon, Sebastiano; Zellinger, Werner; Moser, Bernhard A.; Oprea, Alina; Biggio, Battista; Pelillo, Marcello; Roli, Fabio | ACM COMPUTING SURVEYS | - |
| Why adversarial reprogramming works, when it fails, and how to tell the difference | 1-gen-2023 | Zheng, Yang; Feng, Xiaoyi; Xia, Zhaoqiang; Jiang, Xiaoyue; Demontis, Ambra; Pintor, Maura; Biggio, Battista; Roli, Fabio | INFORMATION SCIENCES | - |
| 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 | - |
| Adversarial Attacks Against Uncertainty Quantification | 1-gen-2023 | Ledda, Emanuele; Angioni, Daniele; Piras, Giorgio; Fumera, Giorgio; Biggio, Battista; Roli, Fabio | - | IEEE COMPUTER SOC |
| Hardening RGB-D object recognition systems against adversarial patch attacks | 1-gen-2023 | Zheng, Yang; Demetrio, Luca; Cinà, Antonio Emanuele; Feng, Xiaoyi; Xia, Zhaoqiang; Jiang, Xiaoyue; Demontis, Ambra; Biggio, Battista; Roli, Fabio | INFORMATION SCIENCES | - |
| Tessellation-Filtering ReLU Neural Networks | 1-gen-2022 | Moser, Bernhard A.; Lewandowski, Michal; Kargaran, Somayeh; Zellinger, Werner; Biggio, Battista; Koutschan, Christoph | - | - |
| Industrial practitioners' mental models of adversarial machine learning | 1-gen-2022 | Bieringer, L.; Grosse, K.; Backes, M.; Biggio, B.; Krombholz, K. | - | USENIX Association |
| 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 | - |
| 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 |
| Explainability-based Debugging of Machine Learning for Vulnerability Discovery | 1-gen-2022 | Sotgiu, Angelo; Pintor, Maura; Biggio, Battista | - | ACM, Association for Computing Machinery |
| Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware | 1-gen-2022 | Demetrio, L; Biggio, B; Roli, F | IEEE SECURITY & PRIVACY | - |
| 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 | - |
| 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 | - |
| Robust Machine Learning for Malware Detection over Time | 1-gen-2022 | Angioni, Daniele; Demetrio, Luca; Pintor, Maura; Biggio, Battista | - | - |
| 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 | - |
| FADER: Fast Adversarial Example Rejection | 1-gen-2022 | Crecchi, Francesco; Melis, Marco; Sotgiu, Angelo; Bacciu, Davide; Biggio, Battista | NEUROCOMPUTING | - |
| secml: Secure and explainable machine learning in Python | 1-gen-2022 | Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Melis, Marco; Demontis, Ambra; Biggio, Battista | SOFTWAREX | - |
| Explaining Machine Learning DGA Detectors from DNS Traffic Data | 1-gen-2022 | Piras, Giorgio; Pintor, Maura; Demetrio, Luca; 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 | - |
| Poisoning attacks on cyber attack detectors for industrial control systems | 1-gen-2021 | Kravchik, Moshe; Biggio, Battista; Shabtai, Asaf | - | - |
| Slope: A First-order Approach for Measuring Gradient Obfuscation | 1-gen-2021 | Pintor, M.; Demetrio, L.; Manca, G.; Biggio, B.; Roli, F. | - | - |
| Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection | 1-gen-2021 | Demetrio, L.; Coull, S. E.; Biggio, B.; Lagorio, G.; Armando, A.; Roli, F. | ACM TRANSACTIONS ON PRIVACY AND SECURITY | - |
| Adversarial Machine Learning: Attacks From Laboratories to the Real World | 1-gen-2021 | Lin, Hsiao-Ying; Biggio, Battista | COMPUTER | - |
| 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 | - |
| The hammer and the nut: is bilevel optimization really needed to poison linear classifiers? | 1-gen-2021 | Cina, A. E.; Vascon, S.; Demontis, A.; Biggio, B.; Roli, F.; Pelillo, M. | - | IEEE, Institute of Electrical and Electronics Engineers |
| 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 | - |
| Fast minimum-norm adversarial attacks through adaptive norm constraints | 1-gen-2021 | Pintor, Maura; Roli, Fabio; Brendel, Wieland; Biggio, Battista | - | - |
| 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. | - | - |
| Task-Specific Automation in Deep Learning Processes | 1-gen-2021 | Buchgeher, G.; Czech, G.; Ribeiro, A. S.; Kloihofer, W.; Meloni, P.; Busia, P.; Deriu, G.; Pintor, M.; Biggio, B.; Chesta, C.; Rinelli, L.; Solans, D.; Portela, M. | - | Springer Science and Business Media Deutschland GmbH |
| Poisoning Attacks on Algorithmic Fairness | 1-gen-2021 | Solans, D.; Biggio, B.; Castillo, C. | - | Springer Science and Business Media Deutschland GmbH |
| 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 | - |
| Adversarial Detection of Flash Malware: Limitations and Open Issues | 1-gen-2020 | Maiorca, D.; Demontis, A.; Biggio, B.; Roli, F.; Giacinto, G. | COMPUTERS & SECURITY | - |
| Explaining vulnerabilities of deep learning to adversarial malware binaries | 1-gen-2019 | Demetrio, Luca; Biggio, Battista; Lagorio, Giovanni; Roli, Fabio; Armando, Alessandro | - | - |
| Deep Learning and Security Workshop 2019 | 1-gen-2019 | Rieck, K.; Biggio, B.; Vasiloglou, N. | - | - |
Legenda icone
- file ad accesso aperto
- file disponibili sulla rete interna
- file disponibili agli utenti autorizzati
- file disponibili solo agli amministratori
- file sotto embargo
- nessun file disponibile