Publications

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2020
D. Maiorca, Demontis, A., Biggio, B., Roli, F., e Giacinto, G., «Adversarial Detection of Flash Malware: Limitations and Open Issues», Computers & Security, vol 96, 2020. (1.08 MB)
A. Sotgiu, Demontis, A., Melis, M., Biggio, B., Fumera, G., Feng, X., e Roli, F., «Deep Neural Rejection against Adversarial Examples», EURASIP Journal on Information Security, vol 5, 2020.
R. Delussu, Putzu, L., e Fumera, G., «An Empirical Evaluation of Cross-scene Crowd Counting Performance», in Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - VISAPP, Valletta - Malta, 2020, vol 4, pagg 373-380. (527.29 KB)
F. Cara, Scalas, M., Giacinto, G., e Maiorca, D., «On the Feasibility of Adversarial Sample Creation Using the Android System API», Information, n° 11(9): 433, 2020. (1.26 MB)
R. Soleymani, Granger, E., e Fumera, G., «F-Measure Curves: A Tool to Visualize Classifier Performance Under Imbalance», Pattern Recognition, vol 100, pag 107146, 2020. (3.15 MB)
R. Delussu, Putzu, L., e Fumera, G., «Investigating Synthetic Data Sets for Crowd Counting in Cross-scene Scenarios», in Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISAPP 2020, Valletta - Malta, 2020, vol 4, pagg 365-372. (4.23 MB)
2021
H. - Y. Lin e Biggio, B., «Adversarial Machine Learning: Attacks From Laboratories to the Real World», Computer, vol 54, pagg 56-60, 2021.
P. Temple, Perrouin, G., Acher, M., Biggio, B., Jézéquel, J. - M., e Roli, F., «Empirical Assessment of Generating Adversarial Configurations for Software Product Lines», Empirical Software Engineering, vol 26, n° 6, 2021. (1.29 MB)
L. Demetrio, Biggio, B., Lagorio, G., Roli, F., e Armando, A., «Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware», IEEE Transactions on Information Forensics and Security, vol 16, pagg 3469-3478, 2021.
D. Solans, Biggio, B., e Castillo, C., «Poisoning Attacks on Algorithmic Fairness», in Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020), 2021, pag 162--177. (1.05 MB)
In Press
W. W. Y. Ng, Hu, J., Yeung, D., Yin, S., e 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., e 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)
Y. Guan, Li, C. - T., e 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)

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