Giorgio Giacinto
Giorgio Giacinto
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Evasion attacks against machine learning at test time
B Biggio, I Corona, D Maiorca, B Nelson, N Šrndić, P Laskov, G Giacinto, ...
Joint European conference on machine learning and knowledge discovery in …, 2013
Design of effective neural network ensembles for image classification purposes
G Giacinto, F Roli
Image and Vision Computing 19 (9-10), 699-707, 2001
McPAD: A multiple classifier system for accurate payload-based anomaly detection
R Perdisci, D Ariu, P Fogla, G Giacinto, W Lee
Computer networks 53 (6), 864-881, 2009
Dynamic classifier selection based on multiple classifier behaviour
G Giacinto, F Roli
Pattern Recognition 34 (9), 1879-1882, 2001
Fusion of multiple classifiers for intrusion detection in computer networks
G Giacinto, F Roli, L Didaci
Pattern recognition letters 24 (12), 1795-1803, 2003
Methods for designing multiple classifier systems
F Roli, G Giacinto, G Vernazza
International Workshop on Multiple Classifier Systems, 78-87, 2001
An approach to the automatic design of multiple classifier systems
G Giacinto, F Roli
Pattern recognition letters 22 (1), 25-33, 2001
Intrusion detection in computer networks by a modular ensemble of one-class classifiers
G Giacinto, R Perdisci, M Del Rio, F Roli
Information Fusion 9 (1), 69-82, 2008
Reject option with multiple thresholds
G Fumera, F Roli, G Giacinto
Pattern recognition 33 (12), 2099-2101, 2000
Novel feature extraction, selection and fusion for effective malware family classification
M Ahmadi, D Ulyanov, S Semenov, M Trofimov, G Giacinto
Proceedings of the sixth ACM conference on data and application security and …, 2016
Combination of neural and statistical algorithms for supervised classification of remote-sensing images
G Giacinto, F Roli, L Bruzzone
Pattern Recognition Letters 21 (5), 385-397, 2000
Alarm clustering for intrusion detection systems in computer networks
R Perdisci, G Giacinto, F Roli
Engineering Applications of Artificial Intelligence 19 (4), 429-438, 2006
Adversarial attacks against intrusion detection systems: Taxonomy, solutions and open issues
I Corona, G Giacinto, F Roli
Information Sciences 239, 201-225, 2013
A study on the performances of dynamic classifier selection based on local accuracy estimation
L Didaci, G Giacinto, F Roli, GL Marcialis
Pattern recognition 38 (11), 2188-2191, 2005
Methods for dynamic classifier selection
G Giacinto, F Roli
Proceedings 10th International Conference on Image Analysis and Processing …, 1999
Design of effective multiple classifier systems by clustering of classifiers
G Giacinto, F Roli, G Fumera
Proceedings 15th International Conference on Pattern Recognition. ICPR-2000 …, 2000
HMMPayl: An intrusion detection system based on Hidden Markov Models
D Ariu, R Tronci, G Giacinto
computers & security 30 (4), 221-241, 2011
Droidsieve: Fast and accurate classification of obfuscated android malware
G Suarez-Tangil, SK Dash, M Ahmadi, J Kinder, G Giacinto, L Cavallaro
Proceedings of the Seventh ACM on Conference on Data and Application …, 2017
Early detection of malicious flux networks via large-scale passive DNS traffic analysis
R Perdisci, I Corona, G Giacinto
IEEE Transactions on Dependable and Secure Computing 9 (5), 714-726, 2012
Yes, machine learning can be more secure! a case study on android malware detection
A Demontis, M Melis, B Biggio, D Maiorca, D Arp, K Rieck, I Corona, ...
IEEE Transactions on Dependable and Secure Computing, 2017
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