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Giulio Zizzo

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Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing

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May 01, 2024
Daniel Gibert, Luca Demetrio, Giulio Zizzo, Quan Le, Jordi Planes, Battista Biggio

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A Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing

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Feb 26, 2024
Daniel Gibert, Giulio Zizzo, Quan Le, Jordi Planes

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Differentially Private and Adversarially Robust Machine Learning: An Empirical Evaluation

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Jan 18, 2024
Janvi Thakkar, Giulio Zizzo, Sergio Maffeis

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Domain Adaptation for Time series Transformers using One-step fine-tuning

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Jan 12, 2024
Subina Khanal, Seshu Tirupathi, Giulio Zizzo, Ambrish Rawat, Torben Bach Pedersen

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Elevating Defenses: Bridging Adversarial Training and Watermarking for Model Resilience

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Jan 07, 2024
Janvi Thakkar, Giulio Zizzo, Sergio Maffeis

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Towards a Practical Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via Randomized Smoothing

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Aug 17, 2023
Daniel Gibert, Giulio Zizzo, Quan Le

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Matching Pairs: Attributing Fine-Tuned Models to their Pre-Trained Large Language Models

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Jun 15, 2023
Myles Foley, Ambrish Rawat, Taesung Lee, Yufang Hou, Gabriele Picco, Giulio Zizzo

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Robust Learning Protocol for Federated Tumor Segmentation Challenge

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Dec 16, 2022
Ambrish Rawat, Giulio Zizzo, Swanand Kadhe, Jonathan P. Epperlein, Stefano Braghin

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Certified Federated Adversarial Training

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Dec 20, 2021
Giulio Zizzo, Ambrish Rawat, Mathieu Sinn, Sergio Maffeis, Chris Hankin

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FAT: Federated Adversarial Training

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Dec 03, 2020
Giulio Zizzo, Ambrish Rawat, Mathieu Sinn, Beat Buesser

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