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M. Melis, Demontis, A., Biggio, B., Brown, G., Fumera, G., and Roli, F., Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid, in ICCV 2017 Workshop on Vision in Practice on Autonomous Robots (ViPAR), Venice, Italy, 2017, vol. 2017 IEEE International Conference on Computer Vision Workshops (ICCVW), pp. 751-759. (3.16 MB)
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)
B. Biggio, Pillai, I., Rota Bulò, S., Ariu, D., Pelillo, M., and Roli, F., Is Data Clustering in Adversarial Settings Secure?, in AISec'13: Proceedings of the 2013 ACM Workshop on Artificial Intelligence and Security, Berlin, 2013, pp. 87-98. (300.52 KB)
B. Biggio, Fumera, G., and Roli, F., Bayesian Linear Combination of Neural Networks, in Innovations in Neural Information Paradigms and Applications, vol. 247, M. Bianchini, Maggini, M., Scarselli, F., and Jain, L. C. Springer Berlin / Heidelberg, 2009, pp. 201-230. (435.32 KB)
B. Biggio, Fumera, G., and Roli, F., Bayesian Analysis of Linear Combiners, in 7th Int. Workshop on Multiple Classifier Systems (MCS 2007), Prague, Czech Republic, 2007, vol. 4472, pp. 292-301. (149.24 KB)
B. Biggio, Corona, I., Fumera, G., Giacinto, G., and Roli, F., Bagging classifiers for fighting poisoning attacks in adversarial classification tasks, in Multiple Classifier Systems (MCS 2011), 2011, vol. 6713, pp. 350-359. (231.43 KB)
G. L. Marcialis, Fumera, G., and Biggio, B., Anti-spoofing: Multimodal, in Encyclopedia of Biometrics, S. Z. Li and Jain, A. K. Springer US, 2014, pp. 1-4.
B. Biggio, Fumera, G., and Roli, F., Adversarial Pattern Classification Using Multiple Classifiers and Randomisation, in 12th Joint IAPR International Workshop on Structural and Syntactic Pattern Recognition (SSPR 2008), Orlando, Florida, USA, 2008. (395.38 KB)
B. Biggio, Adversarial Pattern Classification, University of Cagliari, Cagliari (Italy), 2010. (2.65 MB)
B. Kolosnjaji, Demontis, A., Biggio, B., Maiorca, D., Giacinto, G., Eckert, C., and Roli, F., Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables, in 2018 26th European Signal Processing Conference (EUSIPCO), Rome, 2018, pp. 533-537. (674.62 KB)
H. - Y. Lin and Biggio, B., Adversarial Machine Learning: Attacks From Laboratories to the Real World, Computer, vol. 54, pp. 56-60, 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)
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.
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)
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)