Publications

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Conference Paper
A. Demontis, Russu, P., Biggio, B., Fumera, G., e Roli, F., «On Security and Sparsity of Linear Classifiers for Adversarial Settings», in Joint IAPR Int'l Workshop on Structural, Syntactic, and Statistical Pattern Recognition, Merida, Mexico, 2016, vol 10029 of LNCS, pagg 322-332. (425.68 KB)
B. Biggio, Melis, M., Fumera, G., e Roli, F., «Sparse Support Faces», in Int'l Conf. on Biometrics (ICB), 2015, pagg 208-213. (702.84 KB)
A. Demontis, Biggio, B., Fumera, G., e Roli, F., «Super-Sparse Regression for Fast Age Estimation From Faces at Test Time», in 18th Int'l Conf. on Image Analysis and Processing (ICIAP), Genova, Italy, 2015, vol Image Analysis and Processing (ICIAP 2015), pagg 551-562. (678.7 KB)
B. Biggio, Nelson, B., e Laskov, P., «Support Vector Machines Under Adversarial Label Noise», in Journal of Machine Learning Research - Proc. 3rd Asian Conference on Machine Learning (ACML 2011), Taoyuan, Taiwan, 2011, vol 20, pagg 97-112. (533.74 KB)
L. Muñoz-González, Biggio, B., Demontis, A., Paudice, A., Wongrassamee, V., Lupu, E. C., e Roli, F., «Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization», in 10th ACM Workshop on Artificial Intelligence and Security, 2017, pagg 27-38. (4.08 MB)
P. Temple, Acher, M., Perrouin, G., Biggio, B., Jezequel, J. - M., e Roli, F., «Towards Quality Assurance of Software Product Lines with Adversarial Configurations», in Proceedings of the 23rd International Systems and Software Product Line Conference - Volume A, New York, NY, USA, 2019, pagg 277–288. (2.09 MB)
B. Nelson, Biggio, B., e Laskov, P., «Understanding the Risk Factors of Learning in Adversarial Environments», in 4th ACM Workshop on Artificial Intelligence and Security (AISec 2011), Chicago, IL, USA, 2011, pagg 87–92. (132.42 KB)
D. M. Freeman, Jain, S., Duermuth, M., Biggio, B., e Giacinto, G., «Who Are You? A Statistical Approach to Measuring User Authenticity», in Proc. 23rd Annual Network & Distributed System Security Symposium (NDSS), 2016. (764.14 KB)
A. Demontis, Melis, M., Pintor, M., Jagielski, M., Biggio, B., Oprea, A., Nita-Rotaru, C., e Roli, F., «Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks», in 28th Usenix Security Symposium, Santa Clara, California, USA, 2019, vol 28th {USENIX} Security Symposium ({USENIX} Security 19), pag 321--338. (1.09 MB)
Conference Proceedings
I. Corona, Biggio, B., Contini, M., Piras, L., Corda, R., Mereu, M., Mureddu, G., Ariu, D., e Roli, F., «DeltaPhish: Detecting Phishing Webpages in Compromised Websites», 22nd European Symposium on Research in Computer Security (ESORICS), vol 10492. Springer International Publishing, Norway, September 11-15, 2017, pagg 370–388, 2017. (4.13 MB)
A. Demontis, Biggio, B., Fumera, G., Giacinto, G., e Roli, F., «Infinity-norm Support Vector Machines against Adversarial Label Contamination», 1st Italian Conference on CyberSecurity (ITASEC). Venice, Italy , pagg 106-115, 2017. (504.93 KB)
Journal Article
B. Biggio, Fumera, G., Russu, P., Didaci, L., e Roli, F., «Adversarial Biometric Recognition: A Review on Biometric System Security from the Adversarial Machine Learning Perspective», IEEE Signal Processing Magazine, vol 32, n° 5, pagg 31-41, 2015. (751.08 KB)
D. Maiorca, Demontis, A., Biggio, B., Roli, F., e Giacinto, G., «Adversarial Detection of Flash Malware: Limitations and Open Issues», Computers & Security, vol 96, 2020. (1.08 MB)
L. Demetrio, Coull, S. E., Biggio, B., Lagorio, G., Armando, A., e Roli, F., «Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection», ACM Trans. Priv. Secur., vol 24, 2021.
F. Zhang, Chan, P. P. K., Biggio, B., Yeung, D. S., e Roli, F., «Adversarial Feature Selection Against Evasion Attacks», IEEE Transactions on Cybernetics, vol 46, n° 3, pagg 766-777, 2016. (2.12 MB)
H. - Y. Lin e Biggio, B., «Adversarial Machine Learning: Attacks From Laboratories to the Real World», Computer, vol 54, pagg 56-60, 2021.
G. Ennas, Biggio, B., e Di Guardo, M. Chiara, «Data-driven Journal Meta-ranking in Business and Management», Scientometrics, pagg 1-19, 2015. (896.37 KB)
A. Sotgiu, Demontis, A., Melis, M., Biggio, B., Fumera, G., Feng, X., e Roli, F., «Deep Neural Rejection against Adversarial Examples», EURASIP Journal on Information Security, vol 5, 2020.
D. Maiorca e Biggio, B., «Digital Investigation of PDF Files: Unveiling Traces of Embedded Malware», IEEE Security and Privacy: Special Issue on Digital Forensics, vol 17, n° 1, pagg 63-71, 2019. (838.95 KB)
M. Melis, Scalas, M., Demontis, A., Maiorca, D., Biggio, B., Giacinto, G., e Roli, F., «Do Gradient-Based Explanations Tell Anything About Adversarial Robustness to Android Malware?», International Journal of Machine Learning and Cybernetics, vol 13, pagg 217-232, 2022. (1.2 MB)
P. Temple, Perrouin, G., Acher, M., Biggio, B., Jézéquel, J. - M., e Roli, F., «Empirical Assessment of Generating Adversarial Configurations for Software Product Lines», Empirical Software Engineering, vol 26, n° 6, 2021. (1.29 MB)
F. Crecchi, Melis, M., Sotgiu, A., Bacciu, D., e Biggio, B., «FADER: Fast adversarial example rejection», Neurocomputing, vol 470, pagg 257-268, 2022.
L. Demetrio, Biggio, B., Lagorio, G., Roli, F., e Armando, A., «Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware», IEEE Transactions on Information Forensics and Security, vol 16, pagg 3469-3478, 2021.
B. Biggio, Fumera, G., e Roli, F., «Multiple Classifier Systems for Robust Classifier Design in Adversarial Environments», Journal of Machine Learning and Cybernetics, vol 1, pagg 27–41, 2010. (844.91 KB)
B. Biggio, Fumera, G., e Roli, F., «Pattern Recognition Systems under Attack: Design Issues and Research Challenges», Int'l J. Patt. Recogn. Artif. Intell., vol 28, n° 7, pag 1460002, 2014. (1.41 MB)

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