Ambra Demontis

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Battista BiggioFull Professor, University of Cagliari, ItalyGeverifieerd e-mailadres voor unica.it
Fabio RoliProfessor, University of Genova and Cagliari, ItalyGeverifieerd e-mailadres voor unige.it
Maura PintorUniversity of CagliariGeverifieerd e-mailadres voor unica.it
Marco MelisIndividualGeverifieerd e-mailadres voor unica.it
Giorgio GiacintoProfessor, University of CagliariGeverifieerd e-mailadres voor unica.it
Davide MaiorcaAssistant Professor of Computer Engineering at University of Cagliari, ItalyGeverifieerd e-mailadres voor unica.it
Angelo SotgiuAssistant Professor, University of CagliariGeverifieerd e-mailadres voor unica.it
Giorgio FumeraAssociate Professor of Computer Engineering, University of CagliariGeverifieerd e-mailadres voor unica.it
Antonio Emanuele CinàAssistant Professor @ University of GenoaGeverifieerd e-mailadres voor unige.it
Luca DemetrioAssistant Professor at Università degli Studi di GenovaGeverifieerd e-mailadres voor unige.it
Marcello PelilloProfessor of Computer Science, FIEEE, FIAPR, FAAIA, Ca' Foscari University of VeniceGeverifieerd e-mailadres voor dsi.unive.it
Alina OpreaNortheastern UniversityGeverifieerd e-mailadres voor neu.edu
Cristina Nita-RotaruProfessor, Khoury College of Computer Science, Northeastern UniversityGeverifieerd e-mailadres voor northeastern.edu
Matthew JagielskiGoogle DeepMindGeverifieerd e-mailadres voor google.com
Kathrin GrosseIBM ResearchGeverifieerd e-mailadres voor ibm.com
Sebastiano VasconCa' Foscari University of VeniceGeverifieerd e-mailadres voor unive.it
Konrad RieckTechnische Universität BerlinGeverifieerd e-mailadres voor tu-berlin.de
Luis Muñoz-GonzálezSenior Research Scientist, Telefónica ResearchGeverifieerd e-mailadres voor telefonica.com
Emil LupuProfessor of Computer SystemsGeverifieerd e-mailadres voor imperial.ac.uk
Andrea PaudiceAarhus UniversityGeverifieerd e-mailadres voor cs.au.dk

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Ambra Demontis

Assistant Professor at University of Cagliari

Geverifieerd e-mailadres voor unica.it - Homepage

machine learning adversarial machine learning image recognition


Titel Sorteren op citaties Sorteren op jaar Sorteren op titel	Geciteerd door Geciteerd door	Jaar
Towards poisoning of deep learning algorithms with back-gradient optimization L Muñoz-González, B Biggio, A Demontis, A Paudice, V Wongrassamee, ... Proceedings of the 10th ACM workshop on artificial intelligence and security …, 2017	725	2017
Why do adversarial attacks transfer? explaining transferability of evasion and poisoning attacks A Demontis, M Melis, M Pintor, M Jagielski, B Biggio, A Oprea, ... 28th USENIX security symposium (USENIX security 19), 321-338, 2019	474	2019
Adversarial malware binaries: Evading deep learning for malware detection in executables B Kolosnjaji, A Demontis, B Biggio, D Maiorca, G Giacinto, C Eckert, ... 2018 26th European signal processing conference (EUSIPCO), 533-537, 2018	433	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, 2017	358	2017
Is deep learning safe for robot vision? adversarial examples against the icub humanoid M Melis, A Demontis, B Biggio, G Brown, G Fumera, F Roli Proceedings of the IEEE international conference on computer vision …, 2017	126	2017
Wild patterns reloaded: A survey of machine learning security against training data poisoning AE Cinà, K Grosse, A Demontis, S Vascon, W Zellinger, BA Moser, ... ACM Computing Surveys 55 (13s), 1-39, 2023	105	2023
The threat of offensive ai to organizations Y Mirsky, A Demontis, J Kotak, R Shankar, D Gelei, L Yang, X Zhang, ... Computers & Security 124, 103006, 2023	84	2023
Secure kernel machines against evasion attacks P Russu, A Demontis, B Biggio, G Fumera, F Roli Proceedings of the 2016 ACM workshop on artificial intelligence and security …, 2016	78	2016
Deep neural rejection against adversarial examples A Sotgiu, A Demontis, M Melis, B Biggio, G Fumera, X Feng, F Roli EURASIP Journal on Information Security 2020, 1-10, 2020	69	2020
secml: Secure and explainable machine learning in Python M Pintor, L Demetrio, A Sotgiu, M Melis, A Demontis, B Biggio SoftwareX 18, 101095, 2022	63*	2022
ImageNet-Patch: A dataset for benchmarking machine learning robustness against adversarial patches M Pintor, D Angioni, A Sotgiu, L Demetrio, A Demontis, B Biggio, F Roli Pattern Recognition 134, 109064, 2023	49	2023
On security and sparsity of linear classifiers for adversarial settings A Demontis, P Russu, B Biggio, G Fumera, F Roli Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2016	46	2016
Indicators of attack failure: Debugging and improving optimization of adversarial examples M Pintor, L Demetrio, A Sotgiu, A Demontis, N Carlini, B Biggio, F Roli Advances in Neural Information Processing Systems 35, 23063-23076, 2022	38	2022
Machine learning security against data poisoning: Are we there yet? AE Cinà, K Grosse, A Demontis, B Biggio, F Roli, M Pelillo Computer 57 (3), 26-34, 2024	36	2024
Do gradient-based explanations tell anything about adversarial robustness to android malware? M Melis, M Scalas, A Demontis, D Maiorca, B Biggio, G Giacinto, F Roli International journal of machine learning and cybernetics, 1-16, 2022	36	2022
Adversarial detection of flash malware: Limitations and open issues D Maiorca, A Demontis, B Biggio, F Roli, G Giacinto Computers & Security 96, 101901, 2020	34	2020
Domain knowledge alleviates adversarial attacks in multi-label classifiers S Melacci, G Ciravegna, A Sotgiu, A Demontis, B Biggio, M Gori, F Roli IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (12), 9944 …, 2021	32*	2021
Energy-latency attacks via sponge poisoning AE Cinà, A Demontis, B Biggio, F Roli, M Pelillo arXiv preprint arXiv:2203.08147, 2022	22	2022
Why adversarial reprogramming works, when it fails, and how to tell the difference Y Zheng, X Feng, Z Xia, X Jiang, A Demontis, M Pintor, B Biggio, F Roli Information Sciences 632, 130-143, 2023	20	2023
Infinity-norm support vector machines against adversarial label contamination A Demontis, B Biggio, G Fumera, G Giacinto, F Roli CEUR Workshop Proceedings 1816, 106-115, 2017	18	2017

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