Publications

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2018
M. Jagielski, Oprea, A., Biggio, B., Liu, C., Nita-Rotaru, C., and Li, B., “Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning”, in 39th IEEE Symposium on Security and Privacy, 2018. (1.02 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)
2017
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)
P. Piredda, Ariu, D., Biggio, B., Corona, I., Piras, L., Giacinto, G., and Roli, F., “Deepsquatting: Learning-based Typosquatting Detection at Deeper Domain Levels”, in 16th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2017), 2017, vol. 10640 of LNCS, pp. 347-358. (1.21 MB)
I. Corona, Biggio, B., Contini, M., Piras, L., Corda, R., Mereu, M., Mureddu, G., Ariu, D., and 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, pp. 370–388, 2017. (4.13 MB)
D. Maiorca, Russu, P., Corona, I., Biggio, B., and Giacinto, G., “Detection of Malicious Scripting Code through Discriminant and Adversary-Aware API Analysis”, in 1st Italian Conference on CyberSecurity (ITASEC), 2017, vol. 1816, pp. 96-105. (371.53 KB)
A. Demontis, Biggio, B., Fumera, G., Giacinto, G., and Roli, F., “Infinity-norm Support Vector Machines against Adversarial Label Contamination”, 1st Italian Conference on CyberSecurity (ITASEC). Venice, Italy , pp. 106-115, 2017. (504.93 KB)
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)
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)
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)
2016
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)
M. Ahmadi, Biggio, B., Arzt, S., Ariu, D., and Giacinto, G., “Detecting Misuse of Google Cloud Messaging in Android Badware”, in 6th Workshop on Security and Privacy in Smartphones and Mobile Devices (SPSM), Vienna, Austria, 2016, pp. 103-112. (626.38 KB)
B. Biggio, “Machine Learning under Attack: Vulnerability Exploitation and Security Measures (Invited Keynote at IH&MMSec '16)”, in 4th ACM Workshop on Information Hiding & Multimedia Security, Vigo, Spain, 2016, pp. 1-2. (138.98 KB)
P. Russu, Demontis, A., Biggio, B., Fumera, G., and Roli, F., “Secure Kernel Machines against Evasion Attacks”, in 9th ACM Workshop on Artificial Intelligence and Security, Vienna, Austria, 2016, pp. 59-69. (686.41 KB)
A. Demontis, Russu, P., Biggio, B., Fumera, G., and Roli, F., “On Security and Sparsity of Linear Classifiers for Adversarial Settings”, in Joint IAPR Int'l Workshop on Structural, Syntactic, and Statistical Pattern Recognition, Merida, Mexico, 2016, vol. 10029 of LNCS, pp. 322-332. (425.68 KB)
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)
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)
2015
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)
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)
M. Melis, Piras, L., Biggio, B., Giacinto, G., Fumera, G., and Roli, F., “Fast Image Classification with Reduced Multiclass Support Vector Machines”, in 18th Int'l Conf. on Image Analysis and Processing, Genova, Italy, 2015, vol. Image Analysis and Processing (ICIAP 2015), pp. 78-88. (829.37 KB)
H. Xiao, Biggio, B., Brown, G., Fumera, G., Eckert, C., and Roli, F., “Is Feature Selection Secure against Training Data Poisoning?”, in 32nd Int'l Conf. on Machine Learning (ICML) - JMLR W&CP, 2015, vol. 32, pp. 1689-1698. (1.54 MB)
B. Biggio, Corona, I., He, Z. - M., Chan, P. P. K., Giacinto, G., Yeung, D. S., and Roli, F., “One-and-a-half-class Multiple Classifier Systems for Secure Learning against Evasion Attacks at Test Time”, in Int'l Workshop on Multiple Classifier Systems (MCS), 2015, vol. 9132, pp. 168-180. (467.23 KB)
B. Biggio, Melis, M., Fumera, G., and Roli, F., “Sparse Support Faces”, in Int'l Conf. on Biometrics (ICB), 2015, pp. 208-213. (702.84 KB)
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)

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