Position Tracking During Human Walking Using an Integrated Wearable Sensing System. - Giulio Zizzo; Lei Ren (Sensors, 2017)

CPS-MT: A Real-Time Cyber-Physical System Monitoring Tool for Security Research. - Martín Barrère; Chris Hankin; Angelo Barboni; Giulio Zizzo; Francesca Boem; Sergio Maffeis; Thomas Parisini (RTCSA, 2018)

Adversarial Machine Learning Beyond the Image Domain. - Giulio Zizzo; Chris Hankin; Sergio Maffeis; Kevin Jones (DAC, 2019)

Deep Latent Defence. - Giulio Zizzo; Chris Hankin; Sergio Maffeis; Kevin Jones (CoRR, 2019)

Intrusion Detection for Industrial Control Systems: Evaluation Analysis and Adversarial Attacks. - Giulio Zizzo; Chris Hankin; Sergio Maffeis; Kevin Jones (CoRR, 2019)

Adversarial Attacks on Time-Series Intrusion Detection for Industrial Control Systems. - Giulio Zizzo; Chris Hankin; Sergio Maffeis; Kevin Jones (TrustCom, 2020)

FAT: Federated Adversarial Training. - Giulio Zizzo; Ambrish Rawat; Mathieu Sinn; Beat Buesser (CoRR, 2020)

Certified Federated Adversarial Training. - Giulio Zizzo; Ambrish Rawat; Mathieu Sinn; Sergio Maffeis; Chris Hankin (CoRR, 2021)

Security and Robustness in Federated Learning. - Ambrish Rawat; Giulio Zizzo; Muhammad Zaid Hameed; Luis Muñoz-González (Federated Learning, 2022)

Machine Learning Platform for Extreme Scale Computing on Compressed IoT Data. - Seshu Tirupathi; Dhaval Salwala; Giulio Zizzo; Ambrish Rawat; Mark Purcell; Søren Kejser Jensen; Christian Thomsen 001; Nguyen Ho; Carlos E. Muñiz-Cuza; Jonas Brusokas; Torben Bach Pedersen; Giorgos Alexiou; et al. (IEEE Big Data, 2022)

Robust Learning Protocol for Federated Tumor Segmentation Challenge. - Ambrish Rawat; Giulio Zizzo; Swanand Kadhe; Jonathan P. Epperlein; Stefano Braghin (BrainLes@MICCAI (2), 2022)

Matching Pairs: Attributing Fine-Tuned Models to their Pre-Trained Large Language Models. - Myles Foley; Ambrish Rawat; Taesung Lee; Yufang Hou; Gabriele Picco; Giulio Zizzo (ACL (1), 2023)

Certified Robustness of Static Deep Learning-based Malware Detectors against Patch and Append Attacks. - Daniel Gibert; Giulio Zizzo; Quan Le (AISec@CCS, 2023)

Towards a Practical Defense Against Adversarial Attacks on Deep Learning-Based Malware Detectors via Randomized Smoothing. - Daniel Gibert; Giulio Zizzo; Quan Le (ESORICS Workshops (2), 2023)

A Wolf in Sheep's Clothing: Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks. - Daniel Gibert; Jordi Planes; Quan Le; Giulio Zizzo (EuroS&P Workshops, 2023)

Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks. - Daniel Gibert; Jordi Planes; Quan Le; Giulio Zizzo (CoRR, 2023)

Elevating Defenses: Bridging Adversarial Training and Watermarking for Model Resilience. - Janvi Thakkar; Giulio Zizzo; Sergio Maffeis (CoRR, 2023)

MoJE: Mixture of Jailbreak Experts, Naive Tabular Classifiers as Guard for Prompt Attacks. - Giandomenico Cornacchia; Giulio Zizzo; Kieran Fraser; Muhammad Zaid Hameed; Ambrish Rawat; Mark Purcell (AIES (1), 2024)

Developing Assurance Cases for Adversarial Robustness and Regulatory Compliance in LLMs. - Tomas Bueno Momcilovic; Dian Balta; Beat Buesser; Giulio Zizzo; Mark Purcell (ISSRE (Workshops), 2024)

Assuring Compliance of LLMs with EUAIA Robustness Demands. - Tomas Bueno Momcilovic; Beat Buesser; Giulio Zizzo; Mark Purcell; Dian Balta (Wirtschaftsinformatik, 2024)

Towards Assurance of LLM Adversarial Robustness using Ontology-Driven Argumentation. - Tomas Bueno Momcilovic; Beat Buesser; Giulio Zizzo; Mark Purcell; Dian Balta (xAI (Late-breaking Work, Demos, Doctoral Consortium), 2024)

Adversarial Robustness of Deep Learning-Based Malware Detectors via (De)Randomized Smoothing. - Daniel Gibert; Giulio Zizzo; Quan Le; Jordi Planes (IEEE Access, 2024)

Domain Adaptation for Time series Transformers using One-step fine-tuning. - Subina Khanal; Seshu Tirupathi; Giulio Zizzo; Ambrish Rawat; Torben Bach Pedersen (CoRR, 2024)

Differentially Private and Adversarially Robust Machine Learning: An Empirical Evaluation. - Janvi Thakkar; Giulio Zizzo; Sergio Maffeis (CoRR, 2024)

A Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing. - Daniel Gibert; Giulio Zizzo; Quan Le; Jordi Planes (CoRR, 2024)

Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing. - Daniel Gibert; Luca Demetrio; Giulio Zizzo; Quan Le; Jordi Planes; Battista Biggio (CoRR, 2024)

Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI. - 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; et al. (CoRR, 2024)

Towards Assuring EU AI Act Compliance and Adversarial Robustness of LLMs. - Tomas Bueno Momcilovic; Beat Buesser; Giulio Zizzo; Mark Purcell; Dian Balta (CoRR, 2024)

Knowledge-Augmented Reasoning for EUAIA Compliance and Adversarial Robustness of LLMs. - Tomas Bueno Momcilovic; Dian Balta; Beat Buesser; Giulio Zizzo; Mark Purcell (CoRR, 2024)

Assessing the Impact of Packing on Machine Learning-Based Malware Detection and Classification Systems. - Daniel Gibert; Nikolaos Totosis; Constantinos Patsakis; Giulio Zizzo; Quan Le (CoRR, 2024)

HarmLevelBench: Evaluating Harm-Level Compliance and the Impact of Quantization on Model Alignment. - Yannis Belkhiter; Giulio Zizzo; Sergio Maffeis (CoRR, 2024)

Granite Guardian. - Inkit Padhi; Manish Nagireddy; Giandomenico Cornacchia; Subhajit Chaudhury; Tejaswini Pedapati; Pierre L. Dognin; Keerthiram Murugesan; Erik Miehling; Martin Santillan Cooper; Kieran Fraser; Giulio Zizzo; Muhammad Zaid Hameed; et al. (CoRR, 2024)

Granite Guardian: Comprehensive LLM Safeguarding. - Inkit Padhi; Manish Nagireddy; Giandomenico Cornacchia; Subhajit Chaudhury; Tejaswini Pedapati; Pierre L. Dognin; Keerthiram Murugesan; Erik Miehling; Martín Santillán Cooper; Kieran Fraser; Giulio Zizzo; Muhammad Zaid Hameed; et al. (NAACL (Industry Track), 2025)

Assessing the impact of packing on static machine learning-based malware detection and classification systems. - Daniel Gibert; Nikolaos Totosis; Constantinos Patsakis; Quan Le; Giulio Zizzo (Comput. Secur., 2025)

Adversarial Prompt Evaluation: Systematic Benchmarking of Guardrails Against Prompt Input Attacks on LLMs. - Giulio Zizzo; Giandomenico Cornacchia; Kieran Fraser; Muhammad Zaid Hameed; Ambrish Rawat; Beat Buesser; Mark Purcell; Pin-Yu Chen; Prasanna Sattigeri; Kush R. Varshney (CoRR, 2025)

MAD-MAX: Modular And Diverse Malicious Attack MiXtures for Automated LLM Red Teaming. - Stefan Schoepf; Muhammad Zaid Hameed; Ambrish Rawat; Kieran Fraser; Giulio Zizzo; Giandomenico Cornacchia; Mark Purcell (CoRR, 2025)

Activated LoRA: Fine-tuned LLMs for Intrinsics. - Kristjan Greenewald; Luis A. Lastras; Thomas Parnell; Vraj Shah; Lucian Popa 001; Giulio Zizzo; R. Chulaka Gunasekara; Ambrish Rawat; David Cox (CoRR, 2025)