Publications

Export 87 results:
Filters: Author is Battista Biggio  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
S
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)
H. Xiao, Biggio, B., Nelson, B., Xiao, H., Eckert, C., and Roli, F., Support Vector Machines under Adversarial Label Contamination, Neurocomputing, Special Issue on Advances in Learning with Label Noise, vol. 160, pp. 53-62, 2015. (2.8 MB)
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)
B. Biggio, Fumera, G., Pillai, I., and Roli, F., A survey and experimental evaluation of image spam filtering techniques, Pattern Recognition Letters, vol. 32, pp. 1436 - 1446, 2011. (2.12 MB)
T
D. Maiorca, Biggio, B., and Giacinto, G., Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks, ACM Computing Surveys, vol. 52, no. 4, 2019. (1.21 MB)
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)
U
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)
W
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)
B. Biggio and Roli, F., Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning, Pattern Recognition, vol. 84, pp. 317-331, 2018. (3.76 MB)

Pages