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2020 – today
- 2024
[j2]Daniel Gibert
, Giulio Zizzo, Quan Le, Jordi Planes:
Adversarial Robustness of Deep Learning-Based Malware Detectors via (De)Randomized Smoothing. IEEE Access 12: 61152-61162 (2024)- [c10]Tomas Bueno Momcilovic, Beat Buesser, Giulio Zizzo, Mark Purcell, Dian Balta:
Towards Assurance of LLM Adversarial Robustness using Ontology-Driven Argumentation. xAI (Late-breaking Work, Demos, Doctoral Consortium) 2024: 121-128 - [i14]Subina Khanal, Seshu Tirupathi, Giulio Zizzo, Ambrish Rawat, Torben Bach Pedersen:
Domain Adaptation for Time series Transformers using One-step fine-tuning. CoRR abs/2401.06524 (2024) - [i13]Janvi Thakkar, Giulio Zizzo, Sergio Maffeis:
Differentially Private and Adversarially Robust Machine Learning: An Empirical Evaluation. CoRR abs/2401.10405 (2024) - [i12]Daniel Gibert, Giulio Zizzo, Quan Le, Jordi Planes:
A Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing. CoRR abs/2402.15267 (2024) - [i11]Daniel Gibert, Luca Demetrio, Giulio Zizzo, Quan Le, Jordi Planes, Battista Biggio:
Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing. CoRR abs/2405.00392 (2024) - [i10]Ambrish Rawat, Stefan Schoepf, Giulio Zizzo, Giandomenico Cornacchia, Muhammad Zaid Hameed, Kieran Fraser, Erik Miehling, Beat Buesser, Elizabeth M. Daly, Mark Purcell, Prasanna Sattigeri, Pin-Yu Chen, Kush R. Varshney:
Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI. CoRR abs/2409.15398 (2024) - 2023
- [c9]Myles Foley, Ambrish Rawat, Taesung Lee, Yufang Hou, Gabriele Picco, Giulio Zizzo:
Matching Pairs: Attributing Fine-Tuned Models to their Pre-Trained Large Language Models. ACL (1) 2023: 7423-7442 - [c8]Daniel Gibert, Giulio Zizzo, Quan Le:
Certified Robustness of Static Deep Learning-based Malware Detectors against Patch and Append Attacks. AISec@CCS 2023: 173-184 - [c7]Daniel Gibert, Giulio Zizzo, Quan Le:
Towards a Practical Defense Against Adversarial Attacks on Deep Learning-Based Malware Detectors via Randomized Smoothing. ESORICS Workshops (2) 2023: 683-699 - [c6]Daniel Gibert, Jordi Planes, Quan Le, Giulio Zizzo:
A Wolf in Sheep's Clothing: Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks. EuroS&P Workshops 2023: 415-426 - [i9]Myles Foley, Ambrish Rawat, Taesung Lee, Yufang Hou, Gabriele Picco, Giulio Zizzo:
Matching Pairs: Attributing Fine-Tuned Models to their Pre-Trained Large Language Models. CoRR abs/2306.09308 (2023) - [i8]Daniel Gibert, Jordi Planes, Quan Le, Giulio Zizzo:
Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks. CoRR abs/2306.09925 (2023) - [i7]Daniel Gibert, Giulio Zizzo, Quan Le:
Towards a Practical Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via Randomized Smoothing. CoRR abs/2308.08906 (2023) - [i6]Janvi Thakkar, Giulio Zizzo, Sergio Maffeis:
Elevating Defenses: Bridging Adversarial Training and Watermarking for Model Resilience. CoRR abs/2312.14260 (2023) - 2022
- [c5]Seshu Tirupathi, Dhaval Salwala, Giulio Zizzo, Ambrish Rawat, Mark Purcell, Søren Kejser Jensen, Christian Thomsen, Nguyen Ho, Carlos E. Muñiz-Cuza, Jonas Brusokas, Torben Bach Pedersen, Giorgos Alexiou, Giorgos Giannopoulos, Panagiotis Gidarakos, Alexandros Kalimeris, Stavros Maroulis, George Papastefanatos, Ioannis Psarros, Vassilis Stamatopoulos, Manolis Terrovitis:
Machine Learning Platform for Extreme Scale Computing on Compressed IoT Data. IEEE Big Data 2022: 3179-3185 - [c4]Ambrish Rawat, Giulio Zizzo, Swanand Kadhe, Jonathan P. Epperlein, Stefano Braghin:
Robust Learning Protocol for Federated Tumor Segmentation Challenge. BrainLes@MICCAI (2) 2022: 183-195 - [p1]Ambrish Rawat, Giulio Zizzo, Muhammad Zaid Hameed, Luis Muñoz-González:
Security and Robustness in Federated Learning. Federated Learning 2022: 363-390 - [i5]Ambrish Rawat, Giulio Zizzo, Swanand Kadhe, Jonathan P. Epperlein, Stefano Braghin:
Robust Learning Protocol for Federated Tumor Segmentation Challenge. CoRR abs/2212.08290 (2022) - 2021
- [i4]Giulio Zizzo, Ambrish Rawat, Mathieu Sinn, Sergio Maffeis, Chris Hankin:
Certified Federated Adversarial Training. CoRR abs/2112.10525 (2021) - 2020
- [c3]Giulio Zizzo, Chris Hankin, Sergio Maffeis, Kevin Jones:
Adversarial Attacks on Time-Series Intrusion Detection for Industrial Control Systems. TrustCom 2020: 899-910 - [i3]Giulio Zizzo, Ambrish Rawat, Mathieu Sinn, Beat Buesser:
FAT: Federated Adversarial Training. CoRR abs/2012.01791 (2020)
2010 – 2019
- 2019
- [c2]Giulio Zizzo, Chris Hankin, Sergio Maffeis, Kevin Jones:
Adversarial Machine Learning Beyond the Image Domain. DAC 2019: 176 - [i2]Giulio Zizzo, Chris Hankin, Sergio Maffeis, Kevin Jones:
Deep Latent Defence. CoRR abs/1910.03916 (2019) - [i1]Giulio Zizzo, Chris Hankin, Sergio Maffeis, Kevin Jones:
Intrusion Detection for Industrial Control Systems: Evaluation Analysis and Adversarial Attacks. CoRR abs/1911.04278 (2019) - 2018
- [c1]Martín Barrère, Chris Hankin, Angelo Barboni, Giulio Zizzo, Francesca Boem, Sergio Maffeis, Thomas Parisini:
CPS-MT: A Real-Time Cyber-Physical System Monitoring Tool for Security Research. RTCSA 2018: 240-241 - 2017
- [j1]Giulio Zizzo, Lei Ren:
Position Tracking During Human Walking Using an Integrated Wearable Sensing System. Sensors 17(12): 2866 (2017)
Coauthor Index
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last updated on 2024-10-22 21:19 CEST by the dblp team
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