Publications

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Conference Paper
A. Demontis, Russu, P., Biggio, B., Fumera, G., and 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, pp. 322-332. (425.68 KB)
B. Biggio, Melis, M., Fumera, G., and Roli, F., “Sparse Support Faces”, in Int'l Conf. on Biometrics (ICB), 2015, pp. 208-213. (702.84 KB)
A. Demontis, Biggio, B., Fumera, G., and 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), pp. 551-562. (678.7 KB)
B. Biggio, Nelson, B., and 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, pp. 97-112. (533.74 KB)
L. Muñoz-González, Biggio, B., Demontis, A., Paudice, A., Wongrassamee, V., Lupu, E. C., and Roli, F., “Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization”, in 10th ACM Workshop on Artificial Intelligence and Security, 2017, pp. 27-38. (4.08 MB)
P. Temple, Acher, M., Perrouin, G., Biggio, B., Jezequel, J. - M., and 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, pp. 277–288. (2.09 MB)
B. Nelson, Biggio, B., and 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, pp. 87–92. (132.42 KB)
D. M. Freeman, Jain, S., Duermuth, M., Biggio, B., and 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., and 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), p. 321--338. (1.09 MB)
Conference Proceedings
I. Corona, Biggio, B., Contini, M., Piras, L., Corda, R., Mereu, M., Mureddu, G., Ariu, D., and 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, pp. 370–388, 2017. (4.13 MB)
A. Demontis, Biggio, B., Fumera, G., Giacinto, G., and Roli, F., “Infinity-norm Support Vector Machines against Adversarial Label Contamination”, 1st Italian Conference on CyberSecurity (ITASEC). Venice, Italy , pp. 106-115, 2017. (504.93 KB)
Journal Article
B. Biggio, Fumera, G., Russu, P., Didaci, L., and Roli, F., “Adversarial Biometric Recognition: A Review on Biometric System Security from the Adversarial Machine Learning Perspective”, IEEE Signal Processing Magazine, vol. 32, no. 5, pp. 31-41, 2015. (751.08 KB)
D. Maiorca, Demontis, A., Biggio, B., Roli, F., and 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., and 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., and Roli, F., “Adversarial Feature Selection Against Evasion Attacks”, IEEE Transactions on Cybernetics, vol. 46, no. 3, pp. 766-777, 2016. (2.12 MB)
H. - Y. Lin and Biggio, B., “Adversarial Machine Learning: Attacks From Laboratories to the Real World”, Computer, vol. 54, pp. 56-60, 2021.
G. Ennas, Biggio, B., and Di Guardo, M. Chiara, “Data-driven Journal Meta-ranking in Business and Management”, Scientometrics, pp. 1-19, 2015. (896.37 KB)
A. Sotgiu, Demontis, A., Melis, M., Biggio, B., Fumera, G., Feng, X., and Roli, F., “Deep Neural Rejection against Adversarial Examples”, EURASIP Journal on Information Security, vol. 5, 2020.
D. Maiorca and Biggio, B., “Digital Investigation of PDF Files: Unveiling Traces of Embedded Malware”, IEEE Security and Privacy: Special Issue on Digital Forensics, vol. 17, no. 1, pp. 63-71, 2019. (838.95 KB)
M. Melis, Scalas, M., Demontis, A., Maiorca, D., Biggio, B., Giacinto, G., and Roli, F., “Do Gradient-Based Explanations Tell Anything About Adversarial Robustness to Android Malware?”, International Journal of Machine Learning and Cybernetics, vol. 13, pp. 217-232, 2022. (1.2 MB)
P. Temple, Perrouin, G., Acher, M., Biggio, B., Jézéquel, J. - M., and Roli, F., “Empirical Assessment of Generating Adversarial Configurations for Software Product Lines”, Empirical Software Engineering, vol. 26, no. 6, 2021. (1.29 MB)
F. Crecchi, Melis, M., Sotgiu, A., Bacciu, D., and Biggio, B., “FADER: Fast adversarial example rejection”, Neurocomputing, vol. 470, pp. 257-268, 2022.
L. Demetrio, Biggio, B., Lagorio, G., Roli, F., and Armando, A., “Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware”, IEEE Transactions on Information Forensics and Security, vol. 16, pp. 3469-3478, 2021.
B. Biggio, Fumera, G., and Roli, F., “Multiple Classifier Systems for Robust Classifier Design in Adversarial Environments”, Journal of Machine Learning and Cybernetics, vol. 1, pp. 27–41, 2010. (844.91 KB)
B. Biggio, Fumera, G., and Roli, F., “Pattern Recognition Systems under Attack: Design Issues and Research Challenges”, Int'l J. Patt. Recogn. Artif. Intell., vol. 28, no. 7, p. 1460002, 2014. (1.41 MB)

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