Publications

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A
M. A. A. Dewan, Granger, E., Marcialis, G. L., Sabourin, R., and Roli, F., Adaptive Appearance Model Tracking for Still-to-Video Face Recognition, Pattern Recognition, vol. 49, no. 1, 2016. (6.51 MB)
F. Roli, Didaci, L., and Marcialis, G. L., Adaptive biometric systems that can improve with use, in Advances in Biometrics: Sensors, Systems and Algorithms, R. ;V. N. Govindaraju Springer, 2008, pp. 447-471.
L. Didaci, Marcialis, G. L., and Roli, F., Adaptive Multibiometric Systems, in Multibiometrics for Human Identification, B. Bhanu and Govindaraju, V. Cambridge University Press, 2011.
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)
D. Maiorca, Demontis, A., Biggio, B., Roli, F., and Giacinto, G., Adversarial Detection of Flash Malware: Limitations and Open Issues, Computers & Security, vol. 96, 2020. (1.08 MB)
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)
L. Didaci, Fumera, G., and Roli, F., Analysis of Co-training Algorithm with Very Small Training Sets, in Structural, Syntactic, and Statistical Pattern Recognition, 2012, vol. 7626, pp. 719-726.
L. Didaci, Marcialis, G. L., and Roli, F., Analysis of unsupervised template update in biometric recognition systems, Pattern Recognition Letters, vol. 37, no. 1, 2014. (1.37 MB)
D
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, 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)
A. Sotgiu, Demontis, A., Melis, M., Biggio, B., Fumera, G., Feng, X., and Roli, F., Deep Neural Rejection against Adversarial Examples, EURASIP Journal on Information Security, vol. 5, 2020.
R. Perdisci, Corona, I., Dagon, D., and Lee, W., Detecting Malicious Flux Service Networks through Passive Analysis of Recursive DNS Traces, in Annual Computer Security Applications Conference (ACSAC), Honolulu, Hawaii, USA, 2009. (206.97 KB)
I. Corona and Giacinto, G., Detection of server side web attacks, in Workshop on Applications of Pattern Analysis, Cumberland Lodge, London, UK, 2010. (308.33 KB)
L. Didaci, Fumera, G., and Roli, F., Diversity in classifier ensembles: fertile concept or dead end?, in 11th Int. Workshop on Multiple Classifier Systems, Nanjing, China, 2013, vol. 7872. (241.27 KB) (163.54 KB)
S. Kumar Dash, Suarez-Tangil, G., Khan, S., Tam, K., Ahmadi, M., Kinder, J., and Cavallaro, L., DroidScribe: Classifying Android Malware Based on Runtime Behavior, in Mobile Security Technologies (MoST 2016), 2016. (571.22 KB)
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)
L. Didaci, Dynamic Classifier Selection, Cagliari (Italy), 2005.
L. Didaci and Giacinto, G., Dynamic Classifier Selection by Adaptive k-Nearest-Neighbourhood Rule, in 5th Int. Workshop on Multiple Classifier Systems (MCS 2004), 2004, vol. 3077.
E
M. Fraschini, Hillebrand, A., Demuru, M., Didaci, L., and Marcialis, G. L., An EEG-based biometric system using eigenvector centrality in resting state brain activity, IEEE Signal Processing Letters, vol. 22, no. 6, 2015. (522.35 KB)
M. Fraschini, Hillebrand, A., Demuru, M., Didaci, L., and Marcialis, G. L., An EEG-based biometric system using eigenvector centrality in resting state brain activity, IEEE Signal Processing Letters, vol. 22, no. 6, 2015. (522.35 KB)
R. Delussu, Putzu, L., and 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, pp. 373-380. (527.29 KB)
M. A. O. Ahmed, Didaci, L., Fumera, G., and Roli, F., An Empirical Investigation on the Use of Diversity for Creation of Classifier Ensembles, in Multiple Classifier Systems, 2015, vol. 9132, pp. 206-219. (216.76 KB)

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