Publications

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2019
R. Labaca-Castro, Biggio, B., and Rodosek, G. Dreo, “Poster: Attacking Malware Classifiers by Crafting Gradient-Attacks That Preserve Functionality”, in Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, New York, NY, USA, 2019, pp. 2565–2567.
D. Ugarte, Maiorca, D., Cara, F., and Giacinto, G., “PowerDrive: Accurate De-Obfuscation and Analysis of PowerShell Malware”, 16th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA). Springer, Gothenburg, Sweden, pp. 240-259, 2019. (352.39 KB)
C. Gurrin, Schöffmann, K., Joho, H., Dang-Nguyen, D. - T., Riegler, M., and Piras, L., “Proceedings of the {ACM} Workshop on Lifelog Search Challenge, LSC@ICMR 2019, Ottawa, ON, Canada, 10 June 2019”. ACM, 2019.
C. Di Ruberto, Loddo, A., and Putzu, L., “A region proposal approach for cells detection and counting from microscopic blood images”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11752 LNCS, pp. 47 – 58, 2019.
D. Maiorca, Biggio, B., and Giacinto, G., “Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks”, ACM Computing Surveys, vol. 52, no. 4, 2019. (1.21 MB)
P. Temple, Acher, M., Perrouin, G., Biggio, B., Jezequel, J. - M., and Roli, F., “Towards Quality Assurance of Software Product Lines with Adversarial Configurations”, in Proceedings of the 23rd International Systems and Software Product Line Conference - Volume A, New York, NY, USA, 2019, pp. 277–288. (2.09 MB)
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)
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)
C. Di Ruberto, Putzu, L., and Rodriguez, G., “Fast and accurate computation of orthogonal moments for texture analysis”, Pattern Recognition, vol. 83, pp. 498 – 510, 2018.
R. Soleymani, Granger, E., and Fumera, G., “F-Measure Curves for Visualizing Classifier Performance with Imbalanced Data”, in 8th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR 2018), Siena, 2018. (413.21 KB)
L. Zhou, Piras, L., Riegler, M., Lux, M., Dang-Nguyen, D. - T., and Gurrin, C., “An Interactive Lifelog Retrieval System for Activities of Daily Living Understanding”, in Working Notes of {CLEF} 2018 - Conference and Labs of the Evaluation Forum, Avignon, France, September 10-14, 2018., 2018.
M. Jagielski, Oprea, A., Biggio, B., Liu, C., Nita-Rotaru, C., and Li, B., “Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning”, in 39th IEEE Symposium on Security and Privacy, 2018. (1.02 MB)
B. Lavi, Fumera, G., and Roli, F., “Multi-Stage Ranking Approach for Fast Person Re-Identification”, IET Computer Vision, vol. 12, no. 4, p. 7, 2018. (1.07 MB)
B. Ionescu, Müller, H., Villegas, M., de Herrera, A. García Se, Eickhoff, C., Andrearczyk, V., Cid, Y. Dicente, Liauchuk, V., Kovalev, V., Hasan, S. A., Ling, Y., Farri, O., Liu, J., Lungren, M., Dang-Nguyen, D. - T., Piras, L., Riegler, M., Zhou, L., Lux, M., and Gurrin, C., “Overview of ImageCLEF 2018: Challenges, Datasets and Evaluation”, in Experimental {IR} Meets Multilinguality, Multimodality, and Interaction - 9th International Conference of the {CLEF} Association, {CLEF} 2018, Avignon, France, September 10-14, 2018, Proceedings, 2018, pp. 309–334.
D. - T. Dang-Nguyen, Piras, L., Riegler, M., Zhou, L., Lux, M., and Gurrin, C., “Overview of ImageCLEFlifelog 2018: Daily Living Understanding and Lifelog Moment Retrieval”, in Working Notes of {CLEF} 2018 - Conference and Labs of the Evaluation Forum, Avignon, France, September 10-14, 2018., 2018. (2.01 MB)
C. Gurrin, Schoeffmann, K., Joho, H., Dang-Nguyen, D. - T., Riegler, M., and Piras, L., “Proceedings of the 2018 {ACM} Workshop on The Lifelog Search Challenge, LSC@ICMR 2018, Yokohama, Japan, June 11, 2018”. {ACM}, 2018.
R. Soleymani, Granger, E., and Fumera, G., “Progressive Boosting for Class Imbalance and Its Application to Face Re-Identification”, Expert Systems With Applications, vol. 101, p. 21, 2018. (1.11 MB)
L. Putzu, Piras, L., and Giacinto, G., “Ten years of Relevance Score for Content Based Image Retrieval”, in 14th International Conference Machine Learning and Data Mining (MLDM), New York, 2018, vol. 10935.
S. Porcu, Loddo, A., Putzu, L., and Di Ruberto, C., “White blood cells counting via vector field convolution nuclei segmentation”, in VISIGRAPP 2018 - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2018, vol. 4, pp. 227 – 234.
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)
2017
A. Loddo, Putzu, L., Di Ruberto, C., and Fenu, G., “A Computer-Aided System for Differential Count from Peripheral Blood Cell Images”, in Proceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016, 2017, pp. 112 – 118.
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)

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