Giulio Zizzo
Orcid: 0009-0004-5750-5744
According to our database1,
Giulio Zizzo
authored at least 38 papers
between 2017 and 2025.
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Bibliography
2025
Verifiability and Privacy in Federated Learning through Context-Hiding Multi-Key Homomorphic Authenticators.
CoRR, September, 2025
MAD-MAX: Modular And Diverse Malicious Attack MiXtures for Automated LLM Red Teaming.
CoRR, March, 2025
Adversarial Prompt Evaluation: Systematic Benchmarking of Guardrails Against Prompt Input Attacks on LLMs.
CoRR, February, 2025
Assessing the impact of packing on static machine learning-based malware detection and classification systems.
Comput. Secur., 2025
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025
2024
HarmLevelBench: Evaluating Harm-Level Compliance and the Impact of Quantization on Model Alignment.
CoRR, 2024
Assessing the Impact of Packing on Machine Learning-Based Malware Detection and Classification Systems.
CoRR, 2024
Knowledge-Augmented Reasoning for EUAIA Compliance and Adversarial Robustness of LLMs.
CoRR, 2024
Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI.
CoRR, 2024
Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing.
CoRR, 2024
A Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing.
CoRR, 2024
Differentially Private and Adversarially Robust Machine Learning: An Empirical Evaluation.
CoRR, 2024
CoRR, 2024
Adversarial Robustness of Deep Learning-Based Malware Detectors via (De)Randomized Smoothing.
IEEE Access, 2024
Proceedings of the Joint Proceedings of the xAI 2024 Late-breaking Work, 2024
Proceedings of the 19th International Conference on Wirtschaftsinformatik (WI 2024), 2024
Developing Assurance Cases for Adversarial Robustness and Regulatory Compliance in LLMs.
Proceedings of the 35th IEEE International Symposium on Software Reliability Engineering, 2024
MoJE: Mixture of Jailbreak Experts, Naive Tabular Classifiers as Guard for Prompt Attacks.
Proceedings of the Seventh AAAI/ACM Conference on AI, Ethics, and Society (AIES-24) - Full Archival Papers, October 21-23, 2024, San Jose, California, USA, 2024
2023
Elevating Defenses: Bridging Adversarial Training and Watermarking for Model Resilience.
CoRR, 2023
Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks.
CoRR, 2023
A Wolf in Sheep's Clothing: Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks.
Proceedings of the IEEE European Symposium on Security and Privacy, 2023
Towards a Practical Defense Against Adversarial Attacks on Deep Learning-Based Malware Detectors via Randomized Smoothing.
Proceedings of the Computer Security. ESORICS 2023 International Workshops, 2023
Certified Robustness of Static Deep Learning-based Malware Detectors against Patch and Append Attacks.
Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, 2023
Matching Pairs: Attributing Fine-Tuned Models to their Pre-Trained Large Language Models.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
2022
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2022
Proceedings of the IEEE International Conference on Big Data, 2022
Proceedings of the Federated Learning, 2022
2021
2020
Adversarial Attacks on Time-Series Intrusion Detection for Industrial Control Systems.
Proceedings of the 19th IEEE International Conference on Trust, 2020
2019
Intrusion Detection for Industrial Control Systems: Evaluation Analysis and Adversarial Attacks.
CoRR, 2019
Proceedings of the 56th Annual Design Automation Conference 2019, 2019
2018
Proceedings of the 24th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, 2018
2017
Sensors, 2017