Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Maura Pintor"'
Publikováno v:
SoftwareX, Vol 18, Iss , Pp 101095- (2022)
We present secml, an open-source Python library for secure and explainable machine learning. It implements the most popular attacks against machine learning, including test-time evasion attacks to generate adversarial examples against deep neural net
Externí odkaz:
https://doaj.org/article/565392ef62384406abeb1a89a7961bd8
Autor:
Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Ambra Demontis, Maura Pintor, Battista Biggio, Fabio Roli
Publikováno v:
Information Sciences. 632:130-143
Adversarial reprogramming allows repurposing a machine-learning model to perform a different task. For example, a model trained to recognize animals can be reprogrammed to recognize digits by embedding an adversarial program in the digit images provi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e0138469cc69a4c0f7e22b7dbc37822
https://doi.org/10.1016/j.ins.2023.02.086
https://doi.org/10.1016/j.ins.2023.02.086
Publikováno v:
Proceedings of the 17th International Conference on Availability, Reliability and Security.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::59f20cede26f0b6dc8880fb79c090f56
https://doi.org/10.1145/3538969.3543809
https://doi.org/10.1145/3538969.3543809
Autor:
Maura Pintor, Daniele Angioni, Angelo Sotgiu, Luca Demetrio, Ambra Demontis, Battista Biggio, Fabio Roli
Adversarial patches are optimized contiguous pixel blocks in an input image that cause a machine-learning model to misclassify it. However, their optimization is computationally demanding, and requires careful hyperparameter tuning, potentially leadi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed871e8ab76277d748b3abeb1cb0bc67
Autor:
Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli
Adversarial reprogramming allows stealing computational resources by repurposing machine learning models to perform a different task chosen by the attacker. For example, a model trained to recognize images of animals can be reprogrammed to recognize
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f3d5a2b874eca08cd15a6185a3447b8
Autor:
Yisroel Mirsky, Ambra Demontis, Jaidip Kotak, Ram Shankar, Deng Gelei, Liu Yang, Xiangyu Zhang, Maura Pintor, Wenke Lee, Yuval Elovici, Battista Biggio
Publikováno v:
Computers & Security. 124:103006
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::752ad8a121b5a668b83a3b26d3c79d56
https://doi.org/10.1016/j.cose.2022.103006
https://doi.org/10.1016/j.cose.2022.103006
Publikováno v:
ESANN 2021 proceedings.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c08bf309296c0e635ee2550911ab0d6c
https://doi.org/10.14428/esann/2021.es2021-99
https://doi.org/10.14428/esann/2021.es2021-99
Autor:
Adriano Souza Ribeiro, Georg Buchgeher, Paola Busia, Werner Kloihofer, Luca Rinelli, Gerald Czech, Battista Biggio, David Solans, Cristina Chesta, Manuel Portela, Paolo Meloni, Maura Pintor, Gianfranco Deriu
Publikováno v:
Communications in Computer and Information Science ISBN: 9783030871000
Recent advances in deep learning facilitate the training, testing, and deployment of models through so-called pipelines. Those pipelines are typically orchestrated with general-purpose machine learning frameworks (e.g., Tensorflow Extended), where de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a8182bf1c7f95522fe88b98e38e73909
https://doi.org/10.1007/978-3-030-87101-7_16
https://doi.org/10.1007/978-3-030-87101-7_16
Publikováno v:
Publons
ICPR
ICPR
We present a novel descriptor for crowd behavior analysis and anomaly detection. The goal is to measure by appropriate patterns the speed of formation and disintegration of groups in the crowd. This descriptor is inspired by the concept of one-dimens
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2458278724157474356ba6d6cba1dba0
Publikováno v:
Revista de Tecnologías de la Información y Comunicaciones. :25-27
Industry 4.0 in Mexico, intelligent management in productive systems A disruptive business model is that scheme that has changed according to the new consumer trends of the customers, turning a physical production industry into a form of electronic p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac81d5631ee75ca990affff43c8014d0
https://doi.org/10.35429/jitc.2019.8.3.25.27
https://doi.org/10.35429/jitc.2019.8.3.25.27