基本信息
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职业迁徙
个人简介
My current research interests lie at the intersection of machine learning / AI and security.
I'm particularly interested in the security and robustness of machine learning models. I aim to investigate and develop more robust machine learning algorithms by understanding their vulnerabilities, proposing new algorithms and techniques to defend and mitigate the effect of attacks for enhancing the trustworthiness of machine learning systems.
I actively participate in national and European projects in topics related to both machine learning and cyber-security, including collaboration with other research institutions, universities and companies. Recently, I have participated in MUSKETEER, a collaborative project funded by the European Commission, working with companies like IBM, on the privacy and security of federated machine learning. I have also participated in CONCORDIA, a competence cyber-security network funded also by the European Commission, including about 60 different partners from the academia and the industry. In this project I have worked on robustness of malware detectors based on machine learning against evasion attacks, collborative fraud detection with federated learning, and distributed learning for anomaly detection in IoT.
I'm particularly interested in the security and robustness of machine learning models. I aim to investigate and develop more robust machine learning algorithms by understanding their vulnerabilities, proposing new algorithms and techniques to defend and mitigate the effect of attacks for enhancing the trustworthiness of machine learning systems.
I actively participate in national and European projects in topics related to both machine learning and cyber-security, including collaboration with other research institutions, universities and companies. Recently, I have participated in MUSKETEER, a collaborative project funded by the European Commission, working with companies like IBM, on the privacy and security of federated machine learning. I have also participated in CONCORDIA, a competence cyber-security network funded also by the European Commission, including about 60 different partners from the academia and the industry. In this project I have worked on robustness of malware detectors based on machine learning against evasion attacks, collborative fraud detection with federated learning, and distributed learning for anomaly detection in IoT.
研究兴趣
论文共 37 篇作者统计合作学者相似作者
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COMPUTERS & SECURITY (2023): 103182-103182
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Susanna Bonura, Davide Dalle Carbonare,Roberto Díaz-Morales, Marcos Fernández-Díaz,Lucrezia Morabito,Luis Muñoz-González,Chiara Napione,Ángel Navia-Vázquez,Mark Purcell
Technologies and Applications for Big Data Value (2021)
arxiv(2021)
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4
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arxiv(2020)
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