Publications

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2015
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)
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)
2016
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)
2018
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)
2019
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)
2020
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.
2022
M. Melis, Scalas, M., Demontis, A., Maiorca, D., Biggio, B., Giacinto, G., and Roli, F., “Do Gradient-Based Explanations Tell Anything About Adversarial Robustness to Android Malware?”, International Journal of Machine Learning and Cybernetics, vol. 13, pp. 217-232, 2022. (1.2 MB)
F. Crecchi, Melis, M., Sotgiu, A., Bacciu, D., and Biggio, B., “FADER: Fast adversarial example rejection”, Neurocomputing, vol. 470, pp. 257-268, 2022.
M. Pintor, Demetrio, L., Sotgiu, A., Melis, M., Demontis, A., and Biggio, B., “secml: A Python Library for Secure and Explainable Machine Learning”, SoftwareX, 2022.