Francesco Mercaldo
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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
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
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
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
Diabetes mellitus affected patients classification and diagnosis through machine learning techniques
F Mercaldo, V Nardone, A Santone
Procedia computer science 112, 2519-2528, 2017
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
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
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
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
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
A classifier of malicious android applications
G Canfora, F Mercaldo, CA Visaggio
2013 International Conference on Availability, Reliability and Security, 607-614, 2013
Deep learning for image-based mobile malware detection
F Mercaldo, A Santone
Journal of Computer Virology and Hacking Techniques 16 (2), 157-171, 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
Evaluating convolutional neural network for effective mobile malware detection
F Martinelli, F Marulli, F Mercaldo
Procedia computer science 112, 2372-2381, 2017
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
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
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
Bridemaid: An hybrid tool for accurate detection of android malware
F Martinelli, F Mercaldo, A Saracino
Proceedings of the 2017 ACM on Asia conference on computer and …, 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
Android apps and user feedback: a dataset for software evolution and quality improvement
G Grano, A Di Sorbo, F Mercaldo, CA Visaggio, G Canfora, S Panichella
Proceedings of the 2nd ACM SIGSOFT international workshop on app market …, 2017
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