Publications

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2019
C. Gurrin, Schoeffmann, K., Joho, H., Leibetseder, A., Zhou, L., Duane, A., Dang-Nguyen, D. - T., Riegler, M., Piras, L., Tran, M. - T., Lokoč, J., and Hürst, W., Comparing Approaches to Interactive Lifelog Search at the Lifelog Search Challenge (LSC2018), ITE Transactions on Media Technology and Applications, vol. 7, pp. 46-59, 2019. (4.7 MB)
D. Maiorca and Biggio, B., Digital Investigation of PDF Files: Unveiling Traces of Embedded Malware, IEEE Security and Privacy: Special Issue on Digital Forensics, vol. 17, no. 1, pp. 63-71, 2019. (838.95 KB)
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.
In Press
A. Carcangiu, Spano, L. Davide, Fumera, G., and Roli, F., DEICTIC: a Compositional and Declarative Gesture Description based on Hidden Markov Model, International Journal of Human-Computer Studies, In Press.
F. Crecchi, Bacciu, D., and Biggio, B., Detecting Adversarial Examples through Nonlinear Dimensionality Reduction, in ESANN '19, In Press.
W. W. Y. Ng, Hu, J., Yeung, D., Yin, S., and Roli, F., Diversified Sensitivity based Undersampling for Imbalance Classification Problems, IEEE Transactions on Cybernetics, In Press. (1.91 MB)
G. Suarez-Tangil, Dash, S. Kumar, Ahmadi, M., Kinder, J., Giacinto, G., and Cavallaro, L., DroidSieve: Fast and Accurate Classification of Obfuscated Android Malware, in Proceedings of the Seventh {ACM} Conference on Data and Application Security and Privacy, {CODASPY} 2017, In Press. (478.59 KB)
R. Soleymani, Granger, E., and Fumera, G., Loss Factors for Learning Boosting Ensembles from Imbalanced Data, in 23rd International Conference on Pattern Recognition (ICPR 2016), Cancún, Mexico, In Press.
B. Lavi, Fumera, G., and Roli, F., A Multi-Stage Ranking Approach for Fast Person Re-Identification, IET Computer Vision, In Press. (1.07 MB)
Y. Guan, Li, C. - T., and Roli, F., On Reducing the Effect of Covariate Factors in Gait Recognition: a Classifier Ensemble Method, IEEE Transactions on Pattern Analysis and Machine Intelligence, In Press. (311.43 KB) (151.4 KB)
M. Ahmed, Didaci, L., Fumera, G., Roli, F., and Lavi, B., Using Diversity for Classifier Ensemble Pruning: An Empirical Investigation, Theoretical and Applied Informatics, In Press.
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, In Press. (3.61 MB)

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