Publications

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Conference Paper
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. (1.09 MB)
Conference Proceedings
I. Corona, Biggio, B., Contini, M., Piras, L., Corda, R., Mereu, M., Mureddu, G., Ariu, D., e 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, pagg 370–388, 2017. (4.13 MB)
A. Demontis, Biggio, B., Fumera, G., Giacinto, G., e Roli, F., «Infinity-norm Support Vector Machines against Adversarial Label Contamination», 1st Italian Conference on CyberSecurity (ITASEC). Venice, Italy , pagg 106-115, 2017.
Journal Article
B. Biggio, Fumera, G., Russu, P., Didaci, L., e Roli, F., «Adversarial Biometric Recognition: A Review on Biometric System Security from the Adversarial Machine Learning Perspective», IEEE Signal Processing Magazine, vol 32, n° 5, pagg 31-41, 2015. (751.08 KB)
F. Zhang, Chan, P. P. K., Biggio, B., Yeung, D. S., e Roli, F., «Adversarial Feature Selection Against Evasion Attacks», IEEE Transactions on Cybernetics, vol 46, n° 3, pagg 766-777, 2016. (2.12 MB)
G. Ennas, Biggio, B., e Di Guardo, M. Chiara, «Data-driven Journal Meta-ranking in Business and Management», Scientometrics, pagg 1-19, 2015. (896.37 KB)
D. Maiorca e Biggio, B., «Digital Investigation of PDF Files: Unveiling Traces of Embedded Malware», IEEE Security and Privacy: Special Issue on Digital Forensics, vol 17, n° 1, pagg 63-71, 2019. (838.95 KB)
B. Biggio, Fumera, G., e Roli, F., «Multiple Classifier Systems for Robust Classifier Design in Adversarial Environments», Journal of Machine Learning and Cybernetics, vol 1, pagg 27–41, 2010. (844.91 KB)
B. Biggio, Fumera, G., e Roli, F., «Pattern Recognition Systems under Attack: Design Issues and Research Challenges», Int'l J. Patt. Recogn. Artif. Intell., vol 28, n° 7, pag 1460002, 2014. (1.41 MB)
S. Rota Bulò, Biggio, B., Pillai, I., Pelillo, M., e Roli, F., «Randomized Prediction Games for Adversarial Machine Learning», IEEE Transactions on Neural Networks and Learning Systems, vol 28, n° 11, pagg 2466-2478, 2017. (1.52 MB) (256.21 KB)
B. Biggio, Akhtar, Z., Fumera, G., Marcialis, G. L., e Roli, F., «Security evaluation of biometric authentication systems under real spoofing attacks», IET Biometrics, vol 1, n° 1, pagg 11-24, 2012. (3.21 MB)
B. Biggio, Fumera, G., e Roli, F., «Security evaluation of pattern classifiers under attack», IEEE Transactions on Knowledge and Data Engineering, vol 26, n° 4, pagg 984-996, 2014. (1.35 MB)
B. Biggio, Fumera, G., Marcialis, G. L., e Roli, F., «Statistical Meta-Analysis of Presentation Attacks for Secure Multibiometric Systems», IEEE Transactions on Pattern Analysis and Machine Intelligence, vol 39, n° 3, pagg 561-575, 2017. (5.7 MB)
A. Demontis, Melis, M., Biggio, B., Fumera, G., e Roli, F., «Super-sparse Learning in Similarity Spaces», IEEE Computational Intelligence Magazine, vol 11, n° 4, pagg 36-45, 2016. (555.22 KB)
H. Xiao, Biggio, B., Nelson, B., Xiao, H., Eckert, C., e Roli, F., «Support Vector Machines under Adversarial Label Contamination», Neurocomputing, Special Issue on Advances in Learning with Label Noise, vol 160, pagg 53-62, 2015. (2.8 MB)
B. Biggio, Fumera, G., Pillai, I., e Roli, F., «A survey and experimental evaluation of image spam filtering techniques», Pattern Recognition Letters, vol 32, pagg 1436 - 1446, 2011. (2.12 MB)
D. Maiorca, Biggio, B., e Giacinto, G., «Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks», ACM Computing Surveys, In Press. (1.21 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)
A. Demontis, Melis, M., Biggio, B., Maiorca, D., Arp, D., Rieck, K., Corona, I., Giacinto, G., e Roli, F., «Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection», IEEE Trans. Dependable and Secure Computing, vol 16, n° 4, pagg 711-724, 2019. (3.61 MB)
Magazine Article
B. Biggio, Fumera, G., Pillai, I., Roli, F., e Satta, R., «Evading SpamAssassin with obfuscated text images», Virus Bulletin, n° 11-2007, 2007. (689 KB)
Thesis
B. Biggio, «Adversarial Pattern Classification», University of Cagliari, Cagliari (Italy), 2010. (2.65 MB)

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