Publications

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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)
L. Ghiani, Yambay, D. A., Mura, V., Marcialis, G. L., Roli, F., and Schuckers, S. A., Review of the Fingerprint Liveness Detection (LivDet) competition series: 2009 to 2015, Image and Vision Computing, p. -, 2016.
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)
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)
I. Pillai, Fumera, G., and Roli, F., Designing multi-label classifiers that maximize F measures: state of the art, Pattern Recognition, vol. 61, 2017.
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.
E. Santucci, Didaci, L., Fumera, G., and Roli, F., A Parameter Randomization Approach for Constructing Classifier Ensembles, Pattern Recognition, vol. 69, pp. 1-13, 2017. (448.73 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.
2018
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)
M. Melis, Maiorca, D., Biggio, B., Giacinto, G., and Roli, F., Explaining Black-box Android Malware Detection, in 26th European Signal Processing Conference (EUSIPCO '18), Rome, Italy, 2018, pp. 524-528. (431.78 KB)
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)
2019
L. Demetrio, Biggio, B., Lagorio, G., Roli, F., and Armando, A., Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries, in 3rd Italian Conference on Cyber Security, ITASEC 2019, Pisa, Italy, 2019, vol. 2315.
A. Demontis, Melis, M., Pintor, M., Jagielski, M., Biggio, B., Oprea, A., Nita-Rotaru, C., and 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), p. 321--338. (1.09 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)

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