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ORCIDBattista Biggio
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- affiliation: University of Cagliari, Italy
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2020 – today
- 2023
[j35]Yisroel Mirsky, Ambra Demontis, Jaidip Kotak, Ram Shankar, Gelei Deng, Liu Yang, Xiangyu Zhang, Maura Pintor
, Wenke Lee, Yuval Elovici, Battista Biggio:
The Threat of Offensive AI to Organizations. Comput. Secur. 124: 103006 (2023)- [j34]Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Ambra Demontis, Maura Pintor, Battista Biggio, Fabio Roli:
Why adversarial reprogramming works, when it fails, and how to tell the difference. Inf. Sci. 632: 130-143 (2023) - [j33]Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli:
Stateful detection of adversarial reprogramming. Inf. Sci. 642: 119093 (2023) - [j32]Maura Pintor, Daniele Angioni, Angelo Sotgiu, Luca Demetrio, Ambra Demontis, Battista Biggio, Fabio Roli:
ImageNet-Patch: A dataset for benchmarking machine learning robustness against adversarial patches. Pattern Recognit. 134: 109064 (2023) - [j31]Kathrin Grosse, Lukas Bieringer, Tarek R. Besold, Battista Biggio, Katharina Krombholz:
Machine Learning Security in Industry: A Quantitative Survey. IEEE Trans. Inf. Forensics Secur. 18: 1749-1762 (2023) - [c74]Dario Lazzaro, Antonio Emanuele Cinà, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo:
Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training. ICIAP (2) 2023: 515-526 - [c73]Ambra Demontis, Maura Pintor, Luca Demetrio, Angelo Sotgiu, Daniele Angioni, Giorgio Piras, Srishti Gupta, Battista Biggio, Fabio Roli:
AI Security and Safety: The PRALab Research Experience. Ital-IA 2023: 324-328 - [c72]Maura Pintor, Giulia Orrù, Davide Maiorca, Ambra Demontis, Luca Demetrio, Gian Luca Marcialis, Battista Biggio, Fabio Roli:
Cybersecurity and AI: The PRALab Research Experience. Ital-IA 2023: 426-431 - [c71]Avishag Shapira, Alon Zolfi, Luca Demetrio, Battista Biggio, Asaf Shabtai:
Phantom Sponges: Exploiting Non-Maximum Suppression to Attack Deep Object Detectors. WACV 2023: 4560-4569 - [i61]Dario Lazzaro, Antonio Emanuele Cinà, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo:
Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training. CoRR abs/2307.00368 (2023) - [i60]Biagio Montaruli, Luca Demetrio, Andrea Valenza, Luca Compagna, Davide Ariu, Luca Piras, Davide Balzarotti, Battista Biggio:
Adversarial ModSecurity: Countering Adversarial SQL Injections with Robust Machine Learning. CoRR abs/2308.04964 (2023) - [i59]Yang Zheng, Luca Demetrio, Antonio Emanuele Cinà, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Ambra Demontis, Battista Biggio, Fabio Roli:
Hardening RGB-D Object Recognition Systems against Adversarial Patch Attacks. CoRR abs/2309.07106 (2023) - [i58]Emanuele Ledda, Daniele Angioni, Giorgio Piras, Giorgio Fumera, Battista Biggio, Fabio Roli:
Adversarial Attacks Against Uncertainty Quantification. CoRR abs/2309.10586 (2023) - 2022
- [j30]Kathrin Grosse, Taesung Lee, Battista Biggio, Youngja Park, Michael Backes, Ian M. Molloy:
Backdoor smoothing: Demystifying backdoor attacks on deep neural networks. Comput. Secur. 120: 102814 (2022) - [j29]Moshe Kravchik, Luca Demetrio, Battista Biggio, Asaf Shabtai:
Practical Evaluation of Poisoning Attacks on Online Anomaly Detectors in Industrial Control Systems. Comput. Secur. 122: 102901 (2022) - [j28]Luca Demetrio, Battista Biggio, Fabio Roli:
Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware. IEEE Secur. Priv. 20(5): 77-85 (2022) - [j27]Francesco Crecchi, Marco Melis, Angelo Sotgiu, Davide Bacciu, Battista Biggio:
FADER: Fast adversarial example rejection. Neurocomputing 470: 257-268 (2022) - [j26]Luca Oneto, Nicolò Navarin, Battista Biggio, Federico Errica, Alessio Micheli, Franco Scarselli, Monica Bianchini, Luca Demetrio, Pietro Bongini, Armando Tacchella, Alessandro Sperduti:
Towards learning trustworthily, automatically, and with guarantees on graphs: An overview. Neurocomputing 493: 217-243 (2022) - [j25]Marco Melis, Michele Scalas, Ambra Demontis, Davide Maiorca, Battista Biggio, Giorgio Giacinto, Fabio Roli:
Do gradient-based explanations tell anything about adversarial robustness to android malware? Int. J. Mach. Learn. Cybern. 13(1): 217-232 (2022) - [j24]Stefano Melacci, Gabriele Ciravegna, Angelo Sotgiu, Ambra Demontis, Battista Biggio, Marco Gori, Fabio Roli:
Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9944-9959 (2022) - [j23]Maura Pintor, Luca Demetrio, Angelo Sotgiu, Marco Melis, Ambra Demontis, Battista Biggio:
secml: Secure and explainable machine learning in Python. SoftwareX 18: 101095 (2022) - [c70]Angelo Sotgiu, Maura Pintor, Battista Biggio:
Explainability-based Debugging of Machine Learning for Vulnerability Discovery. ARES 2022: 113:1-113:8 - [c69]Bernhard Alois Moser, Michal Lewandowski, Somayeh Kargaran, Werner Zellinger, Battista Biggio, Christoph Koutschan:
Tessellation-Filtering ReLU Neural Networks. IJCAI 2022: 3335-3341 - [c68]Giorgio Piras, Maura Pintor, Luca Demetrio, Battista Biggio:
Explaining Machine Learning DGA Detectors from DNS Traffic Data. ITASEC 2022: 150-168 - [c67]Daniele Angioni, Luca Demetrio, Maura Pintor, Battista Biggio:
Robust Machine Learning for Malware Detection over Time. ITASEC 2022: 169-180 - [c66]Maura Pintor, Luca Demetrio, Angelo Sotgiu, Ambra Demontis, Nicholas Carlini, Battista Biggio, Fabio Roli:
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples. NeurIPS 2022 - [c65]Lukas Bieringer, Kathrin Grosse, Michael Backes, Battista Biggio, Katharina Krombholz:
Industrial practitioners' mental models of adversarial machine learning. SOUPS @ USENIX Security Symposium 2022: 97-116 - [i57]Maura Pintor, Daniele Angioni, Angelo Sotgiu, Luca Demetrio, Ambra Demontis, Battista Biggio, Fabio Roli:
ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches. CoRR abs/2203.04412 (2022) - [i56]Antonio Emanuele Cinà, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo:
Energy-Latency Attacks via Sponge Poisoning. CoRR abs/2203.08147 (2022) - [i55]Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo:
Machine Learning Security against Data Poisoning: Are We There Yet? CoRR abs/2204.05986 (2022) - [i54]Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Sebastiano Vascon, Werner Zellinger, Bernhard Alois Moser, Alina Oprea, Battista Biggio, Marcello Pelillo, Fabio Roli:
Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning. CoRR abs/2205.01992 (2022) - [i53]Avishag Shapira, Alon Zolfi, Luca Demetrio, Battista Biggio, Asaf Shabtai:
Denial-of-Service Attack on Object Detection Model Using Universal Adversarial Perturbation. CoRR abs/2205.13618 (2022) - [i52]Huang Xiao, Battista Biggio, Blaine Nelson, Han Xiao, Claudia Eckert, Fabio Roli:
Support Vector Machines under Adversarial Label Contamination. CoRR abs/2206.00352 (2022) - [i51]Kathrin Grosse, Lukas Bieringer, Tarek Richard Besold, Battista Biggio, Katharina Krombholz:
"Why do so?" - A Practical Perspective on Machine Learning Security. CoRR abs/2207.05164 (2022) - [i50]Luca Demetrio, Battista Biggio, Fabio Roli:
Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware. CoRR abs/2207.05548 (2022) - [i49]Daniele Angioni, Luca Demetrio, Maura Pintor, Battista Biggio:
Robust Machine Learning for Malware Detection over Time. CoRR abs/2208.04838 (2022) - [i48]Giorgio Piras, Maura Pintor, Luca Demetrio, Battista Biggio:
Explaining Machine Learning DGA Detectors from DNS Traffic Data. CoRR abs/2208.05285 (2022) - [i47]Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli:
Stateful Detection of Adversarial Reprogramming. CoRR abs/2211.02885 (2022) - [i46]Ambra Demontis, Maura Pintor, Luca Demetrio, Kathrin Grosse, Hsiao-Ying Lin, Chengfang Fang, Battista Biggio, Fabio Roli:
A Survey on Reinforcement Learning Security with Application to Autonomous Driving. CoRR abs/2212.06123 (2022) - [i45]Battista Biggio, Nicholas Carlini, Pavel Laskov, Konrad Rieck, Antonio Emanuele Cinà:
Security of Machine Learning (Dagstuhl Seminar 22281). Dagstuhl Reports 12(7): 41-61 (2022) - 2021
- [j22]Hsiao-Ying Lin, Battista Biggio:
Adversarial Machine Learning: Attacks From Laboratories to the Real World. Computer 54(5): 56-60 (2021) - [j21]Paul Temple, Gilles Perrouin, Mathieu Acher, Battista Biggio, Jean-Marc Jézéquel, Fabio Roli:
Empirical assessment of generating adversarial configurations for software product lines. Empir. Softw. Eng. 26(1): 6 (2021) - [j20]Luca Demetrio, Battista Biggio, Giovanni Lagorio, Fabio Roli, Alessandro Armando:
Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware. IEEE Trans. Inf. Forensics Secur. 16: 3469-3478 (2021) - [j19]Luca Demetrio, Scott E. Coull, Battista Biggio, Giovanni Lagorio, Alessandro Armando, Fabio Roli:
Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection. ACM Trans. Priv. Secur. 24(4): 27:1-27:31 (2021) - [c64]Georg Buchgeher, Gerald Czech, Adriano Souza Ribeiro, Werner Kloihofer, Paolo Meloni, Paola Busia, Gianfranco Deriu, Maura Pintor, Battista Biggio, Cristina Chesta, Luca Rinelli, David Solans, Manuel Portela:
Task-Specific Automation in Deep Learning Processes. DEXA Workshops 2021: 159-169 - [c63]Luca Oneto, Nicolò Navarin, Battista Biggio, Federico Errica, Alessio Micheli, Franco Scarselli, Monica Bianchini, Alessandro Sperduti:
Complex Data: Learning Trustworthily, Automatically, and with Guarantees. ESANN 2021 - [c62]Maura Pintor, Luca Demetrio, Giovanni Manca, Battista Biggio, Fabio Roli:
Slope: A First-order Approach for Measuring Gradient Obfuscation. ESANN 2021 - [c61]Antonio Emanuele Cinà, Sebastiano Vascon, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo:
The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers? IJCNN 2021: 1-8 - [c60]Maura Pintor, Fabio Roli, Wieland Brendel, Battista Biggio:
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints. NeurIPS 2021: 20052-20062 - [c59]Moshe Kravchik, Battista Biggio, Asaf Shabtai:
Poisoning attacks on cyber attack detectors for industrial control systems. SAC 2021: 116-125 - [e6]Andrea Torsello, Luca Rossi, Marcello Pelillo, Battista Biggio, Antonio Robles-Kelly:
Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshops, S+SSPR 2020, Padua, Italy, January 21-22, 2021, Proceedings. Lecture Notes in Computer Science 12644, Springer 2021, ISBN 978-3-030-73972-0 [contents] - [i44]Maura Pintor, Fabio Roli, Wieland Brendel, Battista Biggio:
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints. CoRR abs/2102.12827 (2021) - [i43]Antonio Emanuele Cinà, Sebastiano Vascon, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo:
The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers? CoRR abs/2103.12399 (2021) - [i42]Luca Demetrio, Battista Biggio:
secml-malware: A Python Library for Adversarial Robustness Evaluation of Windows Malware Classifiers. CoRR abs/2104.12848 (2021) - [i41]Antonio Emanuele Cinà, Kathrin Grosse, Sebastiano Vascon, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo:
Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions. CoRR abs/2106.07214 (2021) - [i40]Maura Pintor, Luca Demetrio, Angelo Sotgiu, Giovanni Manca, Ambra Demontis, Nicholas Carlini, Battista Biggio, Fabio Roli:
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples. CoRR abs/2106.09947 (2021) - [i39]Yisroel Mirsky, Ambra Demontis, Jaidip Kotak, Ram Shankar, Gelei Deng, Liu Yang, Xiangyu Zhang, Wenke Lee, Yuval Elovici, Battista Biggio:
The Threat of Offensive AI to Organizations. CoRR abs/2106.15764 (2021) - [i38]Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Ambra Demontis, Maura Pintor, Battista Biggio, Fabio Roli:
Why Adversarial Reprogramming Works, When It Fails, and How to Tell the Difference. CoRR abs/2108.11673 (2021) - 2020
- [j18]Davide Maiorca, Ambra Demontis, Battista Biggio, Fabio Roli, Giorgio Giacinto:
Adversarial Detection of Flash Malware: Limitations and Open Issues. Comput. Secur. 96: 101901 (2020) - [j17]Angelo Sotgiu, Ambra Demontis, Marco Melis, Battista Biggio, Giorgio Fumera, Xiaoyi Feng, Fabio Roli:
Deep neural rejection against adversarial examples. EURASIP J. Inf. Secur. 2020: 5 (2020) - [c58]David Solans, Battista Biggio, Carlos Castillo:
Poisoning Attacks on Algorithmic Fairness. ECML/PKDD (1) 2020: 162-177 - [i37]Luca Demetrio, Battista Biggio, Giovanni Lagorio, Fabio Roli, Alessandro Armando:
Efficient Black-box Optimization of Adversarial Windows Malware with Constrained Manipulations. CoRR abs/2003.13526 (2020) - [i36]David Solans, Battista Biggio, Carlos Castillo:
Poisoning Attacks on Algorithmic Fairness. CoRR abs/2004.07401 (2020) - [i35]Marco Melis, Michele Scalas, Ambra Demontis, Davide Maiorca, Battista Biggio, Giorgio Giacinto, Fabio Roli:
Do Gradient-based Explanations Tell Anything About Adversarial Robustness to Android Malware? CoRR abs/2005.01452 (2020) - [i34]Fei Zhang, Patrick P. K. Chan, Battista Biggio, Daniel S. Yeung, Fabio Roli:
Adversarial Feature Selection against Evasion Attacks. CoRR abs/2005.12154 (2020) - [i33]Stefano Melacci, Gabriele Ciravegna, Angelo Sotgiu, Ambra Demontis, Battista Biggio, Marco Gori, Fabio Roli:
Can Domain Knowledge Alleviate Adversarial Attacks in Multi-Label Classifiers? CoRR abs/2006.03833 (2020) - [i32]Luca Demetrio, Scott E. Coull, Battista Biggio, Giovanni Lagorio, Alessandro Armando, Fabio Roli:
Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection. CoRR abs/2008.07125 (2020) - [i31]Francesco Crecchi, Marco Melis, Angelo Sotgiu, Davide Bacciu, Battista Biggio:
FADER: Fast Adversarial Example Rejection. CoRR abs/2010.09119 (2020) - [i30]Moshe Kravchik, Battista Biggio, Asaf Shabtai:
Poisoning Attacks on Cyber Attack Detectors for Industrial Control Systems. CoRR abs/2012.15740 (2020)
2010 – 2019
- 2019
- [j16]Davide Maiorca, Battista Biggio, Giorgio Giacinto:
Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks. ACM Comput. Surv. 52(4): 78:1-78:36 (2019) - [j15]Davide Maiorca, Battista Biggio:
Digital Investigation of PDF Files: Unveiling Traces of Embedded Malware. IEEE Secur. Priv. 17(1): 63-71 (2019) - [j14]Ambra Demontis, Marco Melis, Battista Biggio, Davide Maiorca, Daniel Arp, Konrad Rieck, Igino Corona, Giorgio Giacinto, Fabio Roli:
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection. IEEE Trans. Dependable Secur. Comput. 16(4): 711-724 (2019) - [c57]Raphael Labaca Castro, Battista Biggio, Gabi Dreo Rodosek:
Poster: Attacking Malware Classifiers by Crafting Gradient-Attacks that Preserve Functionality. CCS 2019: 2565-2567 - [c56]Sadia Afroz, Battista Biggio, Nicholas Carlini, Yuval Elovici, Asaf Shabtai:
AISec'19: 12th ACM Workshop on Artificial Intelligence and Security. CCS 2019: 2707-2708 - [c55]Paolo Meloni, Daniela Loi, Paola Busia, Gianfranco Deriu, Andy D. Pimentel, Dolly Sapra, Todor P. Stefanov, Svetlana Minakova, Francesco Conti, Luca Benini, Maura Pintor, Battista Biggio, Bernhard Moser, Natalia Shepeleva, Nikos Fragoulis, Ilias Theodorakopoulos, Michael Masin, Francesca Palumbo:
Optimization and deployment of CNNs at the edge: the ALOHA experience. CF 2019: 326-332 - [c54]Davide Bacciu, Battista Biggio, Paulo Lisboa, José D. Martín, Luca Oneto, Alfredo Vellido:
Societal Issues in Machine Learning: When Learning from Data is Not Enough. ESANN 2019 - [c53]Francesco Crecchi, Davide Bacciu, Battista Biggio:
Detecting Black-box Adversarial Examples through Nonlinear Dimensionality Reduction. ESANN 2019 - [c52]Luca Demetrio, Battista Biggio, Giovanni Lagorio, Fabio Roli, Alessandro Armando:
Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries. ITASEC 2019 - [c51]Paul Temple, Mathieu Acher, Gilles Perrouin, Battista Biggio, Jean-Marc Jézéquel, Fabio Roli:
Towards quality assurance of software product lines with adversarial configurations. SPLC (A) 2019: 38:1-38:12 - [c50]Ambra Demontis, Marco Melis, Maura Pintor, Matthew Jagielski, Battista Biggio, Alina Oprea, Cristina Nita-Rotaru, Fabio Roli:
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks. USENIX Security Symposium 2019: 321-338 - [e5]Lorenzo Cavallaro, Johannes Kinder, Sadia Afroz, Battista Biggio, Nicholas Carlini, Yuval Elovici, Asaf Shabtai:
Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security, AISec@CCS 2019, London, UK, November 15, 2019. ACM 2019, ISBN 978-1-4503-6833-9 [contents] - [i29]Luca Demetrio, Battista Biggio, Giovanni Lagorio, Fabio Roli, Alessandro Armando:
Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries. CoRR abs/1901.03583 (2019) - [i28]Francesco Crecchi, Davide Bacciu, Battista Biggio:
Detecting Adversarial Examples through Nonlinear Dimensionality Reduction. CoRR abs/1904.13094 (2019) - [i27]Paul Temple, Mathieu Acher, Gilles Perrouin, Battista Biggio, Jean-Marc Jézéquel, Fabio Roli:
Towards Quality Assurance of Software Product Lines with Adversarial Configurations. CoRR abs/1909.07283 (2019) - [i26]Angelo Sotgiu, Ambra Demontis, Marco Melis, Battista Biggio, Giorgio Fumera, Xiaoyi Feng, Fabio Roli:
Deep Neural Rejection against Adversarial Examples. CoRR abs/1910.00470 (2019) - [i25]Marco Melis, Ambra Demontis, Maura Pintor, Angelo Sotgiu, Battista Biggio:
secml: A Python Library for Secure and Explainable Machine Learning. CoRR abs/1912.10013 (2019) - 2018
- [j13]Battista Biggio, Fabio Roli:
Wild patterns: Ten years after the rise of adversarial machine learning. Pattern Recognit. 84: 317-331 (2018) - [c49]Sadia Afroz, Battista Biggio, Yuval Elovici, David Freeman, Asaf Shabtai:
11th International Workshop on Artificial Intelligence and Security (AISec 2018). CCS 2018: 2166-2167 - [c48]Battista Biggio:
Session details: AI Security / Adversarial Machine Learning. AISec@CCS 2018 - [c47]Battista Biggio, Fabio Roli:
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning. CCS 2018: 2154-2156 - [c46]Paolo Meloni, Daniela Loi, Gianfranco Deriu, Andy D. Pimentel, Dolly Sapra, Bernhard Moser, Natalia Shepeleva, Francesco Conti, Luca Benini, Oscar Ripolles, David Solans, Maura Pintor, Battista Biggio, Todor P. Stefanov, Svetlana Minakova, Nikolaos Fragoulis, Ilias Theodorakopoulos, Michael Masin, Francesca Palumbo:
ALOHA: an architectural-aware framework for deep learning at the edge. INTESA@ESWEEK 2018: 19-26 - [c45]Marco Melis, Davide Maiorca, Battista Biggio, Giorgio Giacinto, Fabio Roli:
Explaining Black-box Android Malware Detection. EUSIPCO 2018: 524-528 - [c44]Bojan Kolosnjaji, Ambra Demontis, Battista Biggio, Davide Maiorca, Giorgio Giacinto, Claudia Eckert, Fabio Roli:
Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables. EUSIPCO 2018: 533-537 - [c43]Paolo Meloni, Daniela Loi, Gianfranco Deriu, Andy D. Pimentel, Dolly Sapra, Maura Pintor, Battista Biggio, Oscar Ripolles, David Solans, Francesco Conti, Luca Benini, Todor P. Stefanov, Svetlana Minakova, Bernhard Moser, Natalia Shepeleva, Michael Masin, Francesca Palumbo, Nikos Fragoulis, Ilias Theodorakopoulos:
Architecture-aware design and implementation of CNN algorithms for embedded inference: the ALOHA project. ICM 2018: 52-55 - [c42]Matthew Jagielski, Alina Oprea, Battista Biggio, Chang Liu, Cristina Nita-Rotaru, Bo Li:
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning. IEEE Symposium on Security and Privacy 2018: 19-35 - [e4]Sadia Afroz, Battista Biggio, Yuval Elovici, David Freeman, Asaf Shabtai:
Proceedings of the 11th ACM Workshop on Artificial Intelligence and Security, CCS 2018, Toronto, ON, Canada, October 19, 2018. ACM 2018, ISBN 978-1-4503-6004-3 [contents] - [e3]Xiao Bai, Edwin R. Hancock, Tin Kam Ho, Richard C. Wilson, Battista Biggio, Antonio Robles-Kelly:
Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, S+SSPR 2018, Beijing, China, August 17-19, 2018, Proceedings. Lecture Notes in Computer Science 11004, Springer 2018, ISBN 978-3-319-97784-3 [contents] - [i24]Marco Melis, Davide Maiorca, Battista Biggio, Giorgio Giacinto, Fabio Roli:
Explaining Black-box Android Malware Detection. CoRR abs/1803.03544 (2018) - [i23]Bojan Kolosnjaji, Ambra Demontis, Battista Biggio, Davide Maiorca, Giorgio Giacinto, Claudia Eckert, Fabio Roli:
Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables. CoRR abs/1803.04173 (2018) - [i22]Matthew Jagielski, Alina Oprea, Battista Biggio, Chang Liu, Cristina Nita-Rotaru, Bo Li:
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning. CoRR abs/1804.00308 (2018) - [i21]Huang Xiao, Battista Biggio, Gavin Brown, Giorgio Fumera, Claudia Eckert, Fabio Roli:
Is feature selection secure against training data poisoning? CoRR abs/1804.07933 (2018) - [i20]Paul Temple, Mathieu Acher, Battista Biggio, Jean-Marc Jézéquel, Fabio Roli:
Towards Adversarial Configurations for Software Product Lines. CoRR abs/1805.12021 (2018) - [i19]Ambra Demontis, Marco Melis, Maura Pintor, Matthew Jagielski, Battista Biggio, Alina Oprea, Cristina Nita-Rotaru, Fabio Roli:
On the Intriguing Connections of Regularization, Input Gradients and Transferability of Evasion and Poisoning Attacks. CoRR abs/1809.02861 (2018) - [i18]Davide Maiorca, Battista Biggio, Giorgio Giacinto:
Towards Robust Detection of Adversarial Infection Vectors: Lessons Learned in PDF Malware. CoRR abs/1811.00830 (2018) - [i17]Battista Biggio, Ignazio Pillai, Samuel Rota Bulò, Davide Ariu, Marcello Pelillo, Fabio Roli:
Is Data Clustering in Adversarial Settings Secure? CoRR abs/1811.09982 (2018) - [i16]Battista Biggio, Konrad Rieck, Davide Ariu, Christian Wressnegger, Igino Corona, Giorgio Giacinto, Fabio Roli:
Poisoning Behavioral Malware Clustering. CoRR abs/1811.09985 (2018) - 2017
- [j12]Battista Biggio, Giorgio Fumera, Gian Luca Marcialis, Fabio Roli:
Statistical Meta-Analysis of Presentation Attacks for Secure Multibiometric Systems. IEEE Trans. Pattern Anal. Mach. Intell. 39(3): 561-575 (2017) - [j11]Samuel Rota Bulò, Battista Biggio, Ignazio Pillai, Marcello Pelillo, Fabio Roli:
Randomized Prediction Games for Adversarial Machine Learning. IEEE Trans. Neural Networks Learn. Syst. 28(11): 2466-2478 (2017) - [c41]Paolo Piredda, Davide Ariu, Battista Biggio, Igino Corona, Luca Piras, Giorgio Giacinto, Fabio Roli:
Deepsquatting: Learning-Based Typosquatting Detection at Deeper Domain Levels. AI*IA 2017: 347-358 - [c40]