| Explainable deep learning for pulmonary disease and coronavirus COVID-19 detection from X-rays L Brunese, F Mercaldo, A Reginelli, A Santone Computer Methods and Programs in Biomedicine 196, 105608, 2020 | 620 | 2020 |
| Classification of ransomware families with machine learning based onN-gram of opcodes H Zhang, X Xiao, F Mercaldo, S Ni, F Martinelli, AK Sangaiah Future Generation Computer Systems 90, 211-221, 2019 | 289 | 2019 |
| Android malware detection based on system call sequences and LSTM X Xiao, S Zhang, F Mercaldo, G Hu, AK Sangaiah Multimedia Tools and Applications 78, 3979-3999, 2019 | 262 | 2019 |
| Diabetes mellitus affected patients classification and diagnosis through machine learning techniques F Mercaldo, V Nardone, A Santone Procedia computer science 112, 2519-2528, 2017 | 193 | 2017 |
| Detecting android malware using sequences of system calls G Canfora, E Medvet, F Mercaldo, CA Visaggio Proceedings of the 3rd international workshop on software development …, 2015 | 176 | 2015 |
| Effectiveness of opcode ngrams for detection of multi family android malware G Canfora, A De Lorenzo, E Medvet, F Mercaldo, CA Visaggio 2015 10th international conference on availability, reliability and security …, 2015 | 148 | 2015 |
| Ransomware steals your phone. formal methods rescue it F Mercaldo, V Nardone, A Santone, CA Visaggio Formal Techniques for Distributed Objects, Components, and Systems: 36th …, 2016 | 145 | 2016 |
| R-PackDroid: API package-based characterization and detection of mobile ransomware D Maiorca, F Mercaldo, G Giacinto, CA Visaggio, F Martinelli Proceedings of the symposium on applied computing, 1718-1723, 2017 | 143 | 2017 |
| Human behavior characterization for driving style recognition in vehicle system F Martinelli, F Mercaldo, A Orlando, V Nardone, A Santone, AK Sangaiah Computers & Electrical Engineering 83, 102504, 2020 | 134 | 2020 |
| Deep learning for image-based mobile malware detection F Mercaldo, A Santone Journal of Computer Virology and Hacking Techniques 16 (2), 157-171, 2020 | 127 | 2020 |
| An ensemble learning approach for brain cancer detection exploiting radiomic features L Brunese, F Mercaldo, A Reginelli, A Santone Computer methods and programs in biomedicine 185, 105134, 2020 | 127 | 2020 |
| Car hacking identification through fuzzy logic algorithms F Martinelli, F Mercaldo, V Nardone, A Santone 2017 IEEE international conference on fuzzy systems (FUZZ-IEEE), 1-7, 2017 | 120 | 2017 |
| Evaluating convolutional neural network for effective mobile malware detection F Martinelli, F Marulli, F Mercaldo Procedia computer science 112, 2372-2381, 2017 | 106 | 2017 |
| On the effectiveness of system API-related information for Android ransomware detection M Scalas, D Maiorca, F Mercaldo, CA Visaggio, F Martinelli, G Giacinto Computers & Security 86, 168-182, 2019 | 105 | 2019 |
| Towards an interpretable deep learning model for mobile malware detection and family identification G Iadarola, F Martinelli, F Mercaldo, A Santone Computers & Security 105, 102198, 2021 | 102 | 2021 |
| A classifier of malicious android applications G Canfora, F Mercaldo, CA Visaggio 2013 International Conference on Availability, Reliability and Security, 607-614, 2013 | 100 | 2013 |
| Extinguishing ransomware-a hybrid approach to android ransomware detection A Ferrante, M Malek, F Martinelli, F Mercaldo, J Milosevic Foundations and Practice of Security: 10th International Symposium, FPS 2017 …, 2018 | 97 | 2018 |
| Talos: no more ransomware victims with formal methods A Cimitile, F Mercaldo, V Nardone, A Santone, CA Visaggio International Journal of Information Security 17, 719-738, 2018 | 94 | 2018 |
| An hmm and structural entropy based detector for android malware: An empirical study G Canfora, F Mercaldo, CA Visaggio Computers & Security 61, 1-18, 2016 | 89 | 2016 |
| Machine learning for coronavirus covid-19 detection from chest x-rays L Brunese, F Martinelli, F Mercaldo, A Santone Procedia computer science 176, 2212-2221, 2020 | 87 | 2020 |
