Publications

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A
B. Biggio, Fumera, G., Russu, P., Didaci, L., e Roli, F., «Adversarial Biometric Recognition: A Review on Biometric System Security from the Adversarial Machine Learning Perspective», IEEE Signal Processing Magazine, vol 32, n° 5, pagg 31-41, 2015. (751.08 KB)
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)
L. Demetrio, Coull, S. E., Biggio, B., Lagorio, G., Armando, A., e Roli, F., «Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection», ACM Trans. Priv. Secur., vol 24, 2021.
F. Zhang, Chan, P. P. K., Biggio, B., Yeung, D. S., e Roli, F., «Adversarial Feature Selection Against Evasion Attacks», IEEE Transactions on Cybernetics, vol 46, n° 3, pagg 766-777, 2016. (2.12 MB)
H. - Y. Lin e Biggio, B., «Adversarial Machine Learning: Attacks From Laboratories to the Real World», Computer, vol 54, pagg 56-60, 2021.
B. Kolosnjaji, Demontis, A., Biggio, B., Maiorca, D., Giacinto, G., Eckert, C., e Roli, F., «Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables», in 2018 26th European Signal Processing Conference (EUSIPCO), Rome, 2018, pagg 533-537. (674.62 KB)
B. Biggio, «Adversarial Pattern Classification», University of Cagliari, Cagliari (Italy), 2010. (2.65 MB)
B. Biggio, Fumera, G., e Roli, F., «Adversarial Pattern Classification Using Multiple Classifiers and Randomisation», in 12th Joint IAPR International Workshop on Structural and Syntactic Pattern Recognition (SSPR 2008), Orlando, Florida, USA, 2008. (395.38 KB)
G. L. Marcialis, Fumera, G., e Biggio, B., «Anti-spoofing: Multimodal», in Encyclopedia of Biometrics, S. Z. Li e Jain, A. K. Springer US, 2014, pagg 1-4.
B
B. Biggio, Corona, I., Fumera, G., Giacinto, G., e Roli, F., «Bagging classifiers for fighting poisoning attacks in adversarial classification tasks», in Multiple Classifier Systems (MCS 2011), 2011, vol 6713, pagg 350-359. (231.43 KB)
B. Biggio, Fumera, G., e Roli, F., «Bayesian Analysis of Linear Combiners», in 7th Int. Workshop on Multiple Classifier Systems (MCS 2007), Prague, Czech Republic, 2007, vol 4472, pagg 292-301. (149.24 KB)
B. Biggio, Fumera, G., e Roli, F., «Bayesian Linear Combination of Neural Networks», in Innovations in Neural Information Paradigms and Applications, vol 247, M. Bianchini, Maggini, M., Scarselli, F., e Jain, L. C. Springer Berlin / Heidelberg, 2009, pagg 201-230. (435.32 KB)
D
B. Biggio, Pillai, I., Rota Bulò, S., Ariu, D., Pelillo, M., e Roli, F., «Is Data Clustering in Adversarial Settings Secure?», in AISec'13: Proceedings of the 2013 ACM Workshop on Artificial Intelligence and Security, Berlin, 2013, pagg 87-98. (300.52 KB)
G. Ennas, Biggio, B., e Di Guardo, M. Chiara, «Data-driven Journal Meta-ranking in Business and Management», Scientometrics, pagg 1-19, 2015. (896.37 KB)
M. Melis, Demontis, A., Biggio, B., Brown, G., Fumera, G., e 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), pagg 751-759. (3.16 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.
P. Piredda, Ariu, D., Biggio, B., Corona, I., Piras, L., Giacinto, G., e 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, pagg 347-358. (1.21 MB)
I. Corona, Biggio, B., Contini, M., Piras, L., Corda, R., Mereu, M., Mureddu, G., Ariu, D., e Roli, F., «DeltaPhish: Detecting Phishing Webpages in Compromised Websites», 22nd European Symposium on Research in Computer Security (ESORICS), vol 10492. Springer International Publishing, Norway, September 11-15, 2017, pagg 370–388, 2017. (4.13 MB)
B. Biggio, Fumera, G., e Roli, F., «Design of Robust Classifiers for Adversarial Environments», in IEEE International Conference on Systems, Man, and Cybernetics (SMC 2011), Anchorage, Alaska, USA, 2011, pagg 977–982. (328.68 KB)
F. Crecchi, Bacciu, D., e Biggio, B., «Detecting Adversarial Examples through Nonlinear Dimensionality Reduction», in 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - ESANN '19, 2019, pagg 483-488. (552.39 KB)
M. Ahmadi, Biggio, B., Arzt, S., Ariu, D., e Giacinto, G., «Detecting Misuse of Google Cloud Messaging in Android Badware», in 6th Workshop on Security and Privacy in Smartphones and Mobile Devices (SPSM), Vienna, Austria, 2016, pagg 103-112. (626.38 KB)
D. Maiorca, Russu, P., Corona, I., Biggio, B., e Giacinto, G., «Detection of Malicious Scripting Code through Discriminant and Adversary-Aware API Analysis», in 1st Italian Conference on CyberSecurity (ITASEC), 2017, vol 1816, pagg 96-105. (371.53 KB)
D. Maiorca e Biggio, B., «Digital Investigation of PDF Files: Unveiling Traces of Embedded Malware», IEEE Security and Privacy: Special Issue on Digital Forensics, vol 17, n° 1, pagg 63-71, 2019. (838.95 KB)
M. Melis, Scalas, M., Demontis, A., Maiorca, D., Biggio, B., Giacinto, G., e Roli, F., «Do Gradient-Based Explanations Tell Anything About Adversarial Robustness to Android Malware?», International Journal of Machine Learning and Cybernetics, vol 13, pagg 217-232, 2022. (1.2 MB)
E
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)

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