Publications
, “R-PackDroid: Practical On-Device Detection of Android Ransomware”, ArXiv Preprint, Submitted.
(986.09 KB)
(986.09 KB), “DEICTIC: a Compositional and Declarative Gesture Description based on Hidden Markov Model”, International Journal of Human-Computer Studies, In Press.
, “Detecting Adversarial Examples through Nonlinear Dimensionality Reduction”, in ESANN '19, In Press.
, “Diversified Sensitivity based Undersampling for Imbalance Classification Problems”, IEEE Transactions on Cybernetics, In Press. (1.91 MB)
(1.91 MB), “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)
(478.59 KB), “Loss Factors for Learning Boosting Ensembles from Imbalanced Data”, in 23rd International Conference on Pattern Recognition (ICPR 2016), Cancún, Mexico, In Press.
, “A Multi-Stage Ranking Approach for Fast Person Re-Identification”, IET Computer Vision, In Press. (1.07 MB)
(1.07 MB), “On Reducing the Effect of Covariate Factors in Gait Recognition: a Classifier Ensemble Method”, IEEE Transactions on Pattern Analysis and Machine Intelligence, In Press. (311.43 KB) (151.4 KB)
(311.43 KB) (151.4 KB), “Using Diversity for Classifier Ensemble Pruning: An Empirical Investigation”, Theoretical and Applied Informatics, In Press.
, “Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection”, IEEE Trans. Dependable and Secure Computing, In Press. (3.61 MB)
(3.61 MB), “Comparing Approaches to Interactive Lifelog Search at the Lifelog Search Challenge (LSC2018)”, ITE Transactions on Media Technology and Applications, vol. 7, pp. 46-59, 2019. (4.7 MB)
(4.7 MB), “Digital Investigation of PDF Files: Unveiling Traces of Embedded Malware”, IEEE Security and Privacy: Special Issue on Digital Forensics, vol. 17, no. 1, pp. 63-71, 2019. (838.95 KB)
(838.95 KB), “Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries”, in 3rd Italian Conference on Cyber Security, ITASEC 2019, Pisa, Italy, 2019, vol. 2315.
, “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)
(674.62 KB), “Explaining Black-box Android Malware Detection”, in 26th European Signal Processing Conference (EUSIPCO '18), Rome, Italy, 2018, pp. 524-528. (431.78 KB)
(431.78 KB), “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)
(413.21 KB), “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.
, “Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning”, in 39th IEEE Symposium on Security and Privacy, 2018. (1.02 MB)
(1.02 MB), “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.
, “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)
(2.01 MB), “Proceedings of the 2018 {ACM} Workshop on The Lifelog Search Challenge, LSC@ICMR 2018, Yokohama, Japan, June 11, 2018”. {ACM}, 2018.
, “Progressive Boosting for Class Imbalance and Its Application to Face Re-Identification”, Expert Systems With Applications, vol. 101, p. 21, 2018. (1.11 MB)
(1.11 MB), “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.
, “Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning”, Pattern Recognition, vol. 84, pp. 317-331, 2018. (3.76 MB)
(3.76 MB), “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)
(3.16 MB)
