Fabio Martinelli
Cited by
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A survey on security for mobile devices
M La Polla, F Martinelli, D Sgandurra
IEEE communications surveys & tutorials 15 (1), 446-471, 2012
MADAM: a multi-level anomaly detector for android malware
G Dini, F Martinelli, A Saracino, D Sgandurra
International Conference on Mathematical Methods, Models, and Architectures …, 2012
Madam: Effective and efficient behavior-based android malware detection and prevention
A Saracino, D Sgandurra, G Dini, F Martinelli
IEEE Transactions on Dependable and Secure Computing 15 (1), 83-97, 2016
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
Cyber-insurance survey
A Marotta, F Martinelli, S Nanni, A Orlando, A Yautsiukhin
Computer Science Review 24, 35-61, 2017
Usage control in computer security: A survey
A Lazouski, F Martinelli, P Mori
Computer Science Review 4 (2), 81-99, 2010
Non interference for the analysis of cryptographic protocols
R Focardi, R Gorrieri, F Martinelli
International Colloquium on Automata, Languages, and Programming, 354-372, 2000
A uniform approach for the definition of security properties
R Focardi, F Martinelli
International Symposium on Formal Methods, 794-813, 1999
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
Information flow analysis in a discrete-time process algebra
R Focardi, R Gorrieri, F Martinelli
Proceedings 13th IEEE Computer Security Foundations Workshop. CSFW-13, 170-184, 2000
Evaluating convolutional neural network for effective mobile malware detection
F Martinelli, F Marulli, F Mercaldo
Procedia computer science 112, 2372-2381, 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
Analysis of security protocols as open systems
F Martinelli
Theoretical Computer Science 290 (1), 1057-1106, 2003
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
SEAS, a secure e-voting protocol: design and implementation
F Baiardi, A Falleni, R Granchi, F Martinelli, M Petrocchi, A Vaccarelli
Computers & Security 24 (8), 642-652, 2005
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
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
Through modeling to synthesis of security automata
F Martinell, I Matteucci
Electronic Notes in Theoretical Computer Science 179, 31-46, 2007
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