Publications
, «Adversarial Pattern Classification», University of Cagliari, Cagliari (Italy), 2010.
(2.65 MB)
(2.65 MB), «Security of pattern recognition systems in adversarial environments». 2012. (235.41 KB)
(235.41 KB), «Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection», IEEE Trans. Dependable and Secure Computing, vol 16, n° 4, pagg 711-724, 2019. (3.61 MB)
(3.61 MB), «Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning», Pattern Recognition, vol 84, pagg 317-331, 2018. (3.76 MB)
(3.76 MB), «Towards learning trustworthily, automatically, and with guarantees on graphs: An overview», Neurocomputing, vol 493, pagg 217-243, 2022.
, «Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks», ACM Computing Surveys, vol 52, n° 4, 2019. (1.21 MB)
(1.21 MB), «A survey and experimental evaluation of image spam filtering techniques», Pattern Recognition Letters, vol 32, pagg 1436 - 1446, 2011. (2.12 MB)
(2.12 MB), «Support Vector Machines under Adversarial Label Contamination», Neurocomputing, Special Issue on Advances in Learning with Label Noise, vol 160, pagg 53-62, 2015. (2.8 MB)
(2.8 MB), «Super-sparse Learning in Similarity Spaces», IEEE Computational Intelligence Magazine, vol 11, n° 4, pagg 36-45, 2016. (555.22 KB)
(555.22 KB), «Statistical Meta-Analysis of Presentation Attacks for Secure Multibiometric Systems», IEEE Transactions on Pattern Analysis and Machine Intelligence, vol 39, n° 3, pagg 561-575, 2017. (5.7 MB)
(5.7 MB), «Security evaluation of pattern classifiers under attack», IEEE Transactions on Knowledge and Data Engineering, vol 26, n° 4, pagg 984-996, 2014. (1.35 MB)
(1.35 MB), «Security evaluation of biometric authentication systems under real spoofing attacks», IET Biometrics, vol 1, n° 1, pagg 11-24, 2012. (3.21 MB)
(3.21 MB), «secml: A Python Library for Secure and Explainable Machine Learning», SoftwareX, 2022.
, «Randomized Prediction Games for Adversarial Machine Learning», IEEE Transactions on Neural Networks and Learning Systems, vol 28, n° 11, pagg 2466-2478, 2017. (1.52 MB) (256.21 KB)
(1.52 MB) (256.21 KB), «Pattern Recognition Systems under Attack: Design Issues and Research Challenges», Int'l J. Patt. Recogn. Artif. Intell., vol 28, n° 7, pag 1460002, 2014. (1.41 MB)
(1.41 MB), «Multiple Classifier Systems for Robust Classifier Design in Adversarial Environments», Journal of Machine Learning and Cybernetics, vol 1, pagg 27–41, 2010. (844.91 KB)
(844.91 KB), «Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware», IEEE Transactions on Information Forensics and Security, vol 16, pagg 3469-3478, 2021.
, «FADER: Fast adversarial example rejection», Neurocomputing, vol 470, pagg 257-268, 2022.
, «Empirical Assessment of Generating Adversarial Configurations for Software Product Lines», Empirical Software Engineering, vol 26, n° 6, 2021. (1.29 MB)
(1.29 MB), «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)
(1.2 MB), «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)
(838.95 KB), «Deep Neural Rejection against Adversarial Examples», EURASIP Journal on Information Security, vol 5, 2020.
, «Data-driven Journal Meta-ranking in Business and Management», Scientometrics, pagg 1-19, 2015. (896.37 KB)
(896.37 KB), «Adversarial Machine Learning: Attacks From Laboratories to the Real World», Computer, vol 54, pagg 56-60, 2021.
