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Battista Biggio
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- affiliation: University of Cagliari, Italy
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2020 – today
- 2025
- [j44]Andrea Ponte, Dmitrijs Trizna, Luca Demetrio, Battista Biggio, Ivan Tesfai Ogbu, Fabio Roli:
SLIFER: Investigating performance and robustness of malware detection pipelines. Comput. Secur. 150: 104264 (2025) - [j43]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. Neurocomputing 616: 128918 (2025) - 2024
- [j42]Battista Biggio
:
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 - [i77]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) - [i76]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) - [i75]Dmitrijs Trizna, Luca Demetrio, Battista Biggio, Fabio Roli:
Living-off-The-Land Reverse-Shell Detection by Informed Data Augmentation. CoRR abs/2402.18329 (2024) - [i74]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) - [i73]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) - [i72]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) - [i71]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) - [i70]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) - [i69]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) - [i68]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) - [i67]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) - [i66]Emanuele Ledda, Giovanni Scodeller, Daniele Angioni, Giorgio Piras, Antonio Emanuele Cinà, Giorgio Fumera, Battista Biggio, Fabio Roli:
On the Robustness of Adversarial Training Against Uncertainty Attacks. CoRR abs/2410.21952 (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]