Battista Biggio
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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, ...
6th European Machine Learning and Data Mining Conference (ECML/PKDD), 2013
Poisoning Attacks against Support Vector Machines
B Biggio, B Nelson, P Laskov
Int'l Conference on Machine Learning (ICML) - ICML 2022 Test of Time Award, 2012
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning
B Biggio, F Roli
Pattern Recognition (2021 Best Paper Award and Pattern Recognition Medal), 2018
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning
M Jagielski, A Oprea, B Biggio, C Liu, C Nita-Rotaru, B Li
39th IEEE Symposium on Security and Privacy, 2018
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization
L Muńoz-Gonzįlez, B Biggio, A Demontis, A Paudice, V Wongrassamee, ...
10th ACM Workshop on Artificial Intelligence & Security (AISec'17), 2017
Security Evaluation of Pattern Classifiers under Attack
B Biggio, G Fumera, F Roli
IEEE Transactions on Knowledge and Data Engineering 26 (4), 984-996, 2014
Is Feature Selection Secure against Training Data Poisoning?
H Xiao, B Biggio, G Brown, G Fumera, C Eckert, F Roli
Int'l Conference on Machine Learning (ICML), 2015
Support Vector Machines Under Adversarial Label Noise
B Biggio, B Nelson, P Laskov
Journal of Machine Learning Research-Proceedings Track 20, 97-112, 2011
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks
A Demontis, M Melis, M Pintor, M Jagielski, B Biggio, A Oprea, ...
USENIX Security 2019, 2019
Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables
B Kolosnjaji, A Demontis, B Biggio, D Maiorca, G Giacinto, C Eckert, ...
European Signal Processing Conference (EUSIPCO), 2018
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 16 (4), 711-724, 2019
Support Vector Machines under Adversarial Label Contamination
H Xiao, B Biggio, B Nelson, H Xiao, C Eckert, F Roli
Neurocomputing, 2014
Adversarial Feature Selection against Evasion Attacks
F Zhang, PPK Chan, B Biggio, DS Yeung, F Roli
IEEE Transactions on Cybernetics, 2015
Multiple Classifier Systems for Robust Classifier Design in Adversarial Environments
B Biggio, G Fumera, F Roli
International Journal of Machine Learning and Cybernetics 1 (1-4), 27-41, 2010
Security Evaluation of Biometric Authentication Systems under Real Spoofing Attacks
B Biggio, Z Akhtar, G Fumera, GL Marcialis, F Roli
IET biometrics (2014 Premium Award for Best Paper in IET Biometrics), 2012
Poisoning Behavioral Malware Clustering
B Biggio, K Rieck, D Ariu, C Wressnegger, I Corona, G Giacinto, F Roli
Proceedings of the 2014 workshop on artificial intelligent and security …, 2014
Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries
L Demetrio, B Biggio, G Lagorio, F Roli, A Armando
ITASEC 2019, 2019
Is Data Clustering in Adversarial Settings Secure?
B Biggio, I Pillai, S Rota Bulņ, D Ariu, M Pelillo, F Roli
Proceedings of the 2013 ACM workshop on Artificial intelligence and security …, 2013
Functionality-preserving Black-box Optimization of Adversarial Windows Malware
L Demetrio, B Biggio, G Lagorio, F Roli, A Armando
IEEE Transactions on Information Forensics and Security 16, 3469-3478, 2021
Who Are You? A Statistical Approach to Measuring User Authenticity
DM Freeman, S Jain, M Dürmuth, B Biggio, G Giacinto
Proc. 23rd Annual Network & Distributed System Security Symposium (NDSS), 2016
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