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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)
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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)
B. Biggio e Roli, F., «Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning», Pattern Recognition, vol 84, pagg 317-331, 2018. (3.76 MB)

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