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ORCIDBattista Biggio
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- affiliation: University of Cagliari, Italy
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2020 – today
- 2024
[j42]Battista Biggio
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Machine Learning in Computer Security is Difficult to Fix. Commun. ACM 67(11): 103 (2024)- [j41]Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo:
Machine Learning Security Against Data Poisoning: Are We There Yet? Computer 57(3): 26-34 (2024) - [j40]Hamid Eghbal-zadeh, Werner Zellinger, Maura Pintor, Kathrin Grosse, Khaled Koutini, Bernhard Alois Moser, Battista Biggio, Gerhard Widmer:
Rethinking data augmentation for adversarial robustness. Inf. Sci. 654: 119838 (2024) - [j39]Dmitrijs Trizna, Luca Demetrio, Battista Biggio, Fabio Roli:
Nebula: Self-Attention for Dynamic Malware Analysis. IEEE Trans. Inf. Forensics Secur. 19: 6155-6167 (2024) - [j38]Zhishan Li, Hongxu Chen, Battista Biggio, Yifan He, Haoran Cai, Fabio Roli, Lei Xie:
Toward Effective Traffic Sign Detection via Two-Stage Fusion Neural Networks. IEEE Trans. Intell. Transp. Syst. 25(8): 8283-8294 (2024) - [c81]Kathrin Grosse, Lukas Bieringer, Tarek R. Besold, Battista Biggio, Alexandre Alahi:
When Your AI Becomes a Target: AI Security Incidents and Best Practices. AAAI 2024: 23041-23046 - [i76]Antonio Emanuele Cinà, Francesco Villani, Maura Pintor, Lea Schönherr, Battista Biggio, Marcello Pelillo:
σ-zero: Gradient-based Optimization of 𝓁0-norm Adversarial Examples. CoRR abs/2402.01879 (2024) - [i75]Daniele Angioni, Luca Demetrio, Maura Pintor, Luca Oneto, Davide Anguita, Battista Biggio, Fabio Roli:
Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates. CoRR abs/2402.17390 (2024) - [i74]Dmitrijs Trizna, Luca Demetrio, Battista Biggio, Fabio Roli:
Living-off-The-Land Reverse-Shell Detection by Informed Data Augmentation. CoRR abs/2402.18329 (2024) - [i73]Antonio Emanuele Cinà, Jérôme Rony, Maura Pintor, Luca Demetrio, Ambra Demontis, Battista Biggio, Ismail Ben Ayed, Fabio Roli:
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples. CoRR abs/2404.19460 (2024) - [i72]Daniel Gibert, Luca Demetrio, Giulio Zizzo, Quan Le, Jordi Planes, Battista Biggio:
Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing. CoRR abs/2405.00392 (2024) - [i71]Andrea Ponte, Dmitrijs Trizna, Luca Demetrio, Battista Biggio, Ivan Tesfai Ogbu, Fabio Roli:
SLIFER: Investigating Performance and Robustness of Malware Detection Pipelines. CoRR abs/2405.14478 (2024) - [i70]Zhang Chen, Luca Demetrio, Srishti Gupta, Xiaoyi Feng, Zhaoqiang Xia, Antonio Emanuele Cinà, Maura Pintor, Luca Oneto, Ambra Demontis, Battista Biggio, Fabio Roli:
Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis. CoRR abs/2406.10090 (2024) - [i69]Christian Scano, Giuseppe Floris, Biagio Montaruli, Luca Demetrio, Andrea Valenza, Luca Compagna, Davide Ariu, Luca Piras, Davide Balzarotti, Battista Biggio:
ModSec-Learn: Boosting ModSecurity with Machine Learning. CoRR abs/2406.13547 (2024) - [i68]Raffaele Mura, Giuseppe Floris, Luca Scionis, Giorgio Piras, Maura Pintor, Ambra Demontis, Giorgio Giacinto, Battista Biggio, Fabio Roli:
HO-FMN: Hyperparameter Optimization for Fast Minimum-Norm Attacks. CoRR abs/2407.08806 (2024) - [i67]Francesco Villani, Dario Lazzaro, Antonio Emanuele Cinà, Matteo Dell'Amico, Battista Biggio, Fabio Roli:
Sonic: Fast and Transferable Data Poisoning on Clustering Algorithms. CoRR abs/2408.07558 (2024) - [i66]Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio, Giorgio Giacinto, Fabio Roli:
Adversarial Pruning: A Survey and Benchmark of Pruning Methods for Adversarial Robustness. CoRR abs/2409.01249 (2024) - 2023
- [j37]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) - [j36]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. ACM Comput. Surv. 55(13s): 294:1-294:39 (2023) - [j35]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) - [j34]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) - [j33]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. Inf. Sci. 651: 119701 (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) - [c80]Biagio Montaruli, Luca Demetrio, Maura Pintor, Luca Compagna, Davide Balzarotti, Battista Biggio:
Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage Detectors. AISec@CCS 2023: 233-244 - [c79]Maura Pintor, Ambra Demontis, Battista Biggio:
Towards Machine Learning Models that We Can Trust: Testing, Improving, and Explaining Robustness. ESANN 2023 - [c78]Giorgio Piras, Giuseppe Floris, Raffaele Mura, Luca Scionis, Maura Pintor, Battista Biggio, Ambra Demontis:
Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization. ESANN 2023 - [c77]Emanuele Ledda, Daniele Angioni, Giorgio Piras, Giorgio Fumera, Battista Biggio, Fabio Roli:
Adversarial Attacks Against Uncertainty Quantification. ICCV (Workshops) 2023: 4601-4610 - [c76]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 - [c75]Maura Pintor, Luca Demetrio, Angelo Sotgiu, Hsiao-Ying Lin, Chengfang Fang, Ambra Demontis, Battista Biggio:
Detecting Attacks Against Deep Reinforcement Learning for Autonomous Driving. ICMLC 2023: 57-62 - [c74]Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio:
Samples on Thin Ice: Re-Evaluating Adversarial Pruning of Neural Networks. ICMLC 2023: 229-235 - [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 - [i65]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) - [i64]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) - [i63]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) - [i62]Emanuele Ledda, Daniele Angioni, Giorgio Piras, Giorgio Fumera, Battista Biggio, Fabio Roli:
Adversarial Attacks Against Uncertainty Quantification. CoRR abs/2309.10586 (2023) - [i61]Biagio Montaruli, Luca Demetrio, Maura Pintor, Luca Compagna, Davide Balzarotti, Battista Biggio:
Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage Detectors. CoRR abs/2310.03166 (2023) - [i60]Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio:
Samples on Thin Ice: Re-Evaluating Adversarial Pruning of Neural Networks. CoRR abs/2310.08073 (2023) - [i59]Giuseppe Floris, Raffaele Mura, Luca Scionis, Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio:
Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization. CoRR abs/2310.08177 (2023) - [i58]Dmitrijs Trizna, Luca Demetrio, Battista Biggio, Fabio Roli:
Nebula: Self-Attention for Dynamic Malware Analysis. CoRR abs/2310.10664 (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]Luis Muñoz-González, Battista Biggio, Ambra Demontis, Andrea Paudice, Vasin Wongrassamee, Emil C. Lupu, Fabio Roli:
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization. AISec@CCS 2017: 27-38 - [c39]Battista Biggio, David Freeman, Brad Miller, Arunesh Sinha:
10th International Workshop on Artificial Intelligence and Security (AISec 2017). CCS 2017: 2621-2622 - [c38]Igino Corona, Battista Biggio, Matteo Contini, Luca Piras, Roberto Corda, Mauro Mereu, Guido Mureddu, Davide Ariu, Fabio Roli:
DeltaPhish: Detecting Phishing Webpages in Compromised Websites. ESORICS (1) 2017: 370-388 - [c37]Marco Melis, Ambra Demontis, Battista Biggio, Gavin Brown, Giorgio Fumera, Fabio Roli:
Is Deep Learning Safe for Robot Vision? Adversarial Examples Against the iCub Humanoid. ICCV Workshops 2017: 751-759 - [c36]Davide Maiorca, Paolo Russu, Igino Corona, Battista Biggio, Giorgio Giacinto:
Detection of Malicious Scripting Code Through Discriminant and Adversary-Aware API Analysis. ITASEC 2017: 96-105 - [c35]Ambra Demontis, Battista Biggio, Giorgio Fumera, Giorgio Giacinto, Fabio Roli:
Infinity-Norm Support Vector Machines Against Adversarial Label Contamination. ITASEC 2017: 106-115 - [e2]Bhavani Thuraisingham, Battista Biggio, David Mandell Freeman, Brad Miller, Arunesh Sinha:
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security, AISec@CCS 2017, Dallas, TX, USA, November 3, 2017. ACM 2017, ISBN 978-1-4503-5202-4 [contents] - [i15]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. CoRR abs/1704.08996 (2017) - [i14]Igino Corona, Battista Biggio, Matteo Contini, Luca Piras, Roberto Corda, Mauro Mereu, Guido Mureddu, Davide Ariu, Fabio Roli:
DeltaPhish: Detecting Phishing Webpages in Compromised Websites. CoRR abs/1707.00317 (2017) - [i13]Davide Maiorca, Battista Biggio:
Digital Investigation of PDF Files: Unveiling Traces of Embedded Malware. CoRR abs/1707.05102 (2017) - [i12]Battista Biggio, Igino Corona, Davide Maiorca, Blaine Nelson, Nedim Srndic, Pavel Laskov, Giorgio Giacinto, Fabio Roli:
Evasion Attacks against Machine Learning at Test Time. CoRR abs/1708.06131 (2017) - [i11]Marco Melis, Ambra Demontis, Battista Biggio, Gavin Brown, Giorgio Fumera, Fabio Roli:
Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid. CoRR abs/1708.06939 (2017) - [i10]Luis Muñoz-González, Battista Biggio, Ambra Demontis, Andrea Paudice, Vasin Wongrassamee, Emil C. Lupu, Fabio Roli:
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization. CoRR abs/1708.08689 (2017) - [i9]Ambra Demontis, Paolo Russu, Battista Biggio, Giorgio Fumera, Fabio Roli:
On Security and Sparsity of Linear Classifiers for Adversarial Settings. CoRR abs/1709.00045 (2017) - [i8]Battista Biggio, Giorgio Fumera, Fabio Roli:
Security Evaluation of Pattern Classifiers under Attack. CoRR abs/1709.00609 (2017) - [i7]Davide Maiorca, Battista Biggio, Maria Elena Chiappe, Giorgio Giacinto:
Adversarial Detection of Flash Malware: Limitations and Open Issues. CoRR abs/1710.10225 (2017) - [i6]Battista Biggio, Fabio Roli:
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning. CoRR abs/1712.03141 (2017) - [i5]Ambra Demontis, Marco Melis, Battista Biggio, Giorgio Fumera, Fabio Roli:
Super-sparse Learning in Similarity Spaces. CoRR abs/1712.06131 (2017) - 2016
- [j10]Ambra Demontis, Marco Melis, Battista Biggio, Giorgio Fumera, Fabio Roli:
Super-Sparse Learning in Similarity Spaces. IEEE Comput. Intell. Mag. 11(4): 36-45 (2016) - [j9]Fei Zhang, Patrick P. K. Chan, Battista Biggio, Daniel S. Yeung, Fabio Roli:
Adversarial Feature Selection Against Evasion Attacks. IEEE Trans. Cybern. 46(3): 766-777 (2016) - [c34]Paolo Russu, Ambra Demontis, Battista Biggio, Giorgio Fumera, Fabio Roli:
Secure Kernel Machines against Evasion Attacks. AISec@CCS 2016: 59-69 - [c33]Mansour Ahmadi, Battista Biggio, Steven Arzt, Davide Ariu, Giorgio Giacinto:
Detecting Misuse of Google Cloud Messaging in Android Badware. SPSM@CCS 2016: 103-112 - [c32]Battista Biggio:
Machine Learning under Attack: Vulnerability Exploitation and Security Measures. IH&MMSec 2016: 1-2 - [c31]David Freeman, Sakshi Jain, Markus Dürmuth, Battista Biggio, Giorgio Giacinto:
Who Are You? A Statistical Approach to Measuring User Authenticity. NDSS 2016 - [c30]Ambra Demontis, Paolo Russu, Battista Biggio, Giorgio Fumera, Fabio Roli:
On Security and Sparsity of Linear Classifiers for Adversarial Settings. S+SSPR 2016: 322-332 - [e1]Antonio Robles-Kelly, Marco Loog, Battista Biggio, Francisco Escolano, Richard C. Wilson:
Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, S+SSPR 2016, Mérida, Mexico, November 29 - December 2, 2016, Proceedings. Lecture Notes in Computer Science 10029, 2016, ISBN 978-3-319-49054-0 [contents] - [i4]Samuel Rota Bulò, Battista Biggio, Ignazio Pillai, Marcello Pelillo, Fabio Roli:
Randomized Prediction Games for Adversarial Machine Learning. CoRR abs/1609.00804 (2016) - [i3]Battista Biggio, Giorgio Fumera, Gian Luca Marcialis, Fabio Roli:
Statistical Meta-Analysis of Presentation Attacks for Secure Multibiometric Systems. CoRR abs/1609.01461 (2016) - [i2]Igino Corona, Battista Biggio, Davide Maiorca:
AdversariaLib: An Open-source Library for the Security Evaluation of Machine Learning Algorithms Under Attack. CoRR abs/1611.04786 (2016) - 2015
- [j8]Huang Xiao, Battista Biggio, Blaine Nelson, Han Xiao, Claudia Eckert, Fabio Roli:
Support vector machines under adversarial label contamination. Neurocomputing 160: 53-62 (2015) - [j7]Gianfranco Ennas, Battista Biggio, Maria Chiara Di Guardo:
Data-driven journal meta-ranking in business and management. Scientometrics 105(3): 1911-1929 (2015) - [j6]Battista Biggio, Giorgio Fumera, Paolo Russu, Luca Didaci, Fabio Roli:
Adversarial Biometric Recognition : A review on biometric system security from the adversarial machine-learning perspective. IEEE Signal Process. Mag. 32(5): 31-41 (2015) - [c29]Battista Biggio, Marco Melis, Giorgio Fumera, Fabio Roli:
Sparse support faces. ICB 2015: 208-213 - [c28]Marco Melis, Luca Piras, Battista Biggio, Giorgio Giacinto, Giorgio Fumera, Fabio Roli:
Fast Image Classification with Reduced Multiclass Support Vector Machines. ICIAP (2) 2015: 78-88 - [c27]Ambra Demontis, Battista Biggio, Giorgio Fumera, Fabio Roli:
Super-Sparse Regression for Fast Age Estimation from Faces at Test Time. ICIAP (2) 2015: 551-562 - [c26]Huang Xiao, Battista Biggio, Gavin Brown, Giorgio Fumera, Claudia Eckert, Fabio Roli:
Is Feature Selection Secure against Training Data Poisoning? ICML 2015: 1689-1698 - [c25]Battista Biggio, Igino Corona, Zhi-Min He, Patrick P. K. Chan, Giorgio Giacinto, Daniel S. Yeung, Fabio Roli:
One-and-a-Half-Class Multiple Classifier Systems for Secure Learning Against Evasion Attacks at Test Time. MCS 2015: 168-180 - [r1]Gian Luca Marcialis, Battista Biggio, Giorgio Fumera:
Anti-spoofing, Multimodal. Encyclopedia of Biometrics 2015: 103-105 - 2014
- [j5]Battista Biggio, Giorgio Fumera, Fabio Roli:
Pattern Recognition Systems under Attack: Design Issues and Research Challenges. Int. J. Pattern Recognit. Artif. Intell. 28(7) (2014) - [j4]Battista Biggio, Giorgio Fumera, Fabio Roli:
Security Evaluation of PatternClassifiers under Attack. IEEE Trans. Knowl. Data Eng. 26(4): 984-996 (2014) - [c24]Battista Biggio:
On learning and recognition of secure patterns. AISec@CCS 2014: 1-2 - [c23]Battista Biggio, Konrad Rieck, Davide Ariu, Christian Wressnegger, Igino Corona, Giorgio Giacinto, Fabio Roli:
Poisoning behavioral malware clustering. AISec@CCS 2014: 27-36 - [c22]Battista Biggio, Samuel Rota Bulò, Ignazio Pillai, Michele Mura, Eyasu Zemene Mequanint, Marcello Pelillo, Fabio Roli:
Poisoning Complete-Linkage Hierarchical Clustering. S+SSPR 2014: 42-52 - [p3]Giorgio Fumera, Gian Luca Marcialis, Battista Biggio, Fabio Roli, Stephanie A. C. Schuckers:
Multimodal Anti-spoofing in Biometric Recognition Systems. Handbook of Biometric Anti-Spoofing 2014: 165-184 - [i1]Battista Biggio, Igino Corona, Blaine Nelson, Benjamin I. P. Rubinstein, Davide Maiorca, Giorgio Fumera, Giorgio Giacinto, Fabio Roli:
Security Evaluation of Support Vector Machines in Adversarial Environments. CoRR abs/1401.7727 (2014) - 2013
- [c21]Battista Biggio, Ignazio Pillai, Samuel Rota Bulò, Davide Ariu, Marcello Pelillo, Fabio Roli:
Is data clustering in adversarial settings secure? AISec 2013: 87-98 - [c20]Fabio Roli, Battista Biggio, Giorgio Fumera:
Pattern Recognition Systems under Attack. CIARP (1) 2013: 1-8 - [c19]Battista Biggio, Luca Didaci, Giorgio Fumera, Fabio Roli:
Poisoning attacks to compromise face templates. ICB 2013: 1-7 - [c18]Battista Biggio, Igino Corona, Davide Maiorca, Blaine Nelson, Nedim Srndic, Pavel Laskov, Giorgio Giacinto, Fabio Roli:
Evasion Attacks against Machine Learning at Test Time. ECML/PKDD (3) 2013: 387-402 - 2012
- [j3]Battista Biggio, Zahid Akhtar, Giorgio Fumera, Gian Luca Marcialis, Fabio Roli:
Security evaluation of biometric authentication systems under real spoofing attacks. IET Biom. 1(1): 11-24 (2012) - [c17]Battista Biggio, Giorgio Fumera, Fabio Roli:
Learning sparse kernel machines with biometric similarity functions for identity recognition. BTAS 2012: 325-330 - [c16]Battista Biggio, Blaine Nelson, Pavel Laskov:
Poisoning Attacks against Support Vector Machines. ICML 2012 - [c15]Battista Biggio, Giorgio Fumera, Fabio Roli, Luca Didaci:
Poisoning Adaptive Biometric Systems. SSPR/SPR 2012: 417-425 - 2011
- [j2]Battista Biggio, Giorgio Fumera, Ignazio Pillai, Fabio Roli:
A survey and experimental evaluation of image spam filtering techniques. Pattern Recognit. Lett. 32(10): 1436-1446 (2011) - [c14]Zahid Akhtar, Battista Biggio, Giorgio Fumera, Gian Luca Marcialis:
Robustness of multi-modal biometric systems under realistic spoof attacks against all traits. BioMS 2011: 1-6 - [c13]Blaine Nelson, Battista Biggio, Pavel Laskov:
Understanding the risk factors of learning in adversarial environments. AISec 2011: 87-92 - [c12]Battista Biggio, Zahid Akhtar, Giorgio Fumera, Gian Luca Marcialis, Fabio Roli:
Robustness of multi-modal biometric verification systems under realistic spoofing attacks. IJCB 2011: 1-6 - [c11]Battista Biggio, Igino Corona, Giorgio Fumera, Giorgio Giacinto, Fabio Roli:
Bagging Classifiers for Fighting Poisoning Attacks in Adversarial Classification Tasks. MCS 2011: 350-359 - [c10]Battista Biggio, Giorgio Fumera, Fabio Roli:
Design of robust classifiers for adversarial environments. SMC 2011: 977-982 - [c9]Blaine Nelson, Battista Biggio, Pavel Laskov:
Microbagging Estimators: An Ensemble Approach to Distance-weighted Classifiers. ACML 2011: 63-79 - [c8]Battista Biggio, Blaine Nelson, Pavel Laskov:
Support Vector Machines Under Adversarial Label Noise. ACML 2011: 97-112 - 2010
- [j1]Battista Biggio, Giorgio Fumera, Fabio Roli:
Multiple classifier systems for robust classifier design in adversarial environments. Int. J. Mach. Learn. Cybern. 1(1-4): 27-41 (2010) - [c7]Battista Biggio, Giorgio Fumera, Fabio Roli:
Multiple Classifier Systems under Attack. MCS 2010: 74-83
2000 – 2009
- 2009
- [c6]Battista Biggio, Giorgio Fumera, Fabio Roli:
Multiple Classifier Systems for Adversarial Classification Tasks. MCS 2009: 132-141 - [p2]Battista Biggio, Giorgio Fumera, Fabio Roli:
Evade Hard Multiple Classifier Systems. Applications of Supervised and Unsupervised Ensemble Methods 2009: 15-38 - [p1]Battista Biggio, Giorgio Fumera, Fabio Roli:
Bayesian Linear Combination of Neural Networks. Innovations in Neural Information Paradigms and Applications 2009: 201-230 - 2008
- [c5]Giorgio Fumera, Fabio Roli, Battista Biggio, Ignazio Pillai:
Improving Image Spam Filtering Using Image Text Features. CEAS 2008 - [c4]Battista Biggio, Giorgio Fumera, Fabio Roli:
Adversarial Pattern Classification Using Multiple Classifiers and Randomisation. SSPR/SPR 2008: 500-509 - 2007
- [c3]Battista Biggio, Giorgio Fumera, Ignazio Pillai, Fabio Roli:
Image Spam Filtering by Content Obscuring Detection. CEAS 2007 - [c2]Battista Biggio, Giorgio Fumera, Ignazio Pillai, Fabio Roli:
Image Spam Filtering Using Visual Information. ICIAP 2007: 105-110 - [c1]Battista Biggio, Giorgio Fumera, Fabio Roli:
Bayesian Analysis of Linear Combiners. MCS 2007: 292-301
Coauthor Index
[j41] [i73] [i70] [i68] [i66] [j37] [j36] [j35] [j34] [j33] [j32] [c79] [c78] [c76] [c75] [c74] [c73] [c72] [i65] [i63] [i60] [i59] [j25] [j24] [j23] [c66] [i57] [i56] [i55] [i54] [i47] [i46] [c61] [i43] [i41] [i40] [i39] [i38] [j18] [j17] [i35] [i33] [j14] [c50] [i26] [i25] [c44] [i23] [i19] [c40] [c37] [c35] [i15] [i11] [i10] [i9] [i5] [j10] [c34] [c30] [c27]
[j41] [j39] [j38] [i75] [i74] [i73] [i71] [i70] [i68] [i67] [i66] [j36] [j35] [j34] [j33] [j32] [c77] [c76] [c73] [c72] [i65] [i63] [i62] [i58] [j28] [j25] [j24] [c66] [i57] [i56] [i55] [i54] [i52] [i50] [i47] [i46] [j21] [j20] [j19] [c62] [c61] [c60] [i44] [i43] [i41] [i40] [i38] [j18] [j17] [i37] [i35] [i34] [i33] [i32] [j14] [c52] [c51] [c50] [i29] [i27] [i26] [j13] [c47] [c45] [c44] [i24] [i23] [i21] [i20] [i19] [i17] [i16] [j12] [j11] [c41] [c40] [c38] [c37] [c35] [i15] [i14] [i12] [i11] [i10] [i9] [i8] [i6] [i5] [j10] [j9] [c34] [c30] [i4] [i3] [j8] [j6] [c29] [c28] [c27] [c26] [c25] [j5] [j4] [c23] [c22] [p3] [i1] [c21] [c20] [c19] [c18] [j3] [c17] [c15] [j2] [c12] [c11] [c10] [j1] [c7] [c6] [p2] [p1] [c5] [c4] [c3] [c2] [c1]
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