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Journal Article
S. Rota Bulò, Biggio, B., Pillai, I., Pelillo, M., and Roli, F., Randomized Prediction Games for Adversarial Machine Learning, IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 11, pp. 2466-2478, 2017. (1.52 MB) (256.21 KB)
M. Pintor, Demetrio, L., Sotgiu, A., Melis, M., Demontis, A., and Biggio, B., secml: A Python Library for Secure and Explainable Machine Learning, SoftwareX, 2022.
B. Biggio, Akhtar, Z., Fumera, G., Marcialis, G. L., and Roli, F., Security evaluation of biometric authentication systems under real spoofing attacks, IET Biometrics, vol. 1, no. 1, pp. 11-24, 2012. (3.21 MB)
B. Biggio, Fumera, G., and Roli, F., Security evaluation of pattern classifiers under attack, IEEE Transactions on Knowledge and Data Engineering, vol. 26, no. 4, pp. 984-996, 2014. (1.35 MB)
B. Biggio, Fumera, G., Marcialis, G. L., and Roli, F., Statistical Meta-Analysis of Presentation Attacks for Secure Multibiometric Systems, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 3, pp. 561-575, 2017. (5.7 MB)
A. Demontis, Melis, M., Biggio, B., Fumera, G., and Roli, F., Super-sparse Learning in Similarity Spaces, IEEE Computational Intelligence Magazine, vol. 11, no. 4, pp. 36-45, 2016. (555.22 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, 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)
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. Oneto, Navarin, N., Biggio, B., Errica, F., Micheli, A., Scarselli, F., Bianchini, M., Demetrio, L., Bongini, P., Tacchella, A., and Sperduti, A., Towards learning trustworthily, automatically, and with guarantees on graphs: An overview, Neurocomputing, vol. 493, pp. 217-243, 2022.
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)
A. Demontis, Melis, M., Biggio, B., Maiorca, D., Arp, D., Rieck, K., Corona, I., Giacinto, G., and Roli, F., Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection, IEEE Trans. Dependable and Secure Computing, vol. 16, no. 4, pp. 711-724, 2019. (3.61 MB)
Magazine Article
B. Biggio, Fumera, G., Pillai, I., Roli, F., and Satta, R., Evading SpamAssassin with obfuscated text images, Virus Bulletin, no. 11-2007, 2007. (689 KB)
B. Biggio, Adversarial Pattern Classification, University of Cagliari, Cagliari (Italy), 2010. (2.65 MB)