Dario Pasquini

Orcid: 0000-0003-0248-6043

According to our database1, Dario Pasquini authored at least 19 papers between 2019 and 2024.

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Bibliography

2024
Hacking Back the AI-Hacker: Prompt Injection as a Defense Against LLM-driven Cyberattacks.
CoRR, 2024

LLMmap: Fingerprinting For Large Language Models.
CoRR, 2024

Universal Neural-Cracking-Machines: Self-Configurable Password Models from Auxiliary Data.
Proceedings of the IEEE Symposium on Security and Privacy, 2024

Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks.
Proceedings of the 2024 Workshop on Artificial Intelligence and Security, 2024

2023
Breach Extraction Attacks: Exposing and Addressing the Leakage in Second Generation Compromised Credential Checking Services.
IACR Cryptol. ePrint Arch., 2023

Can Decentralized Learning be more robust than Federated Learning?
CoRR, 2023

Your Email Address Holds the Key: Understanding the Connection Between Email and Password Security with Deep Learning.
Proceedings of the 2023 IEEE Security and Privacy Workshops (SPW), 2023

On the (In)security of Peer-to-Peer Decentralized Machine Learning.
Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

2022
On the Privacy of Decentralized Machine Learning.
CoRR, 2022

Eluding Secure Aggregation in Federated Learning via Model Inconsistency.
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

2021
Enabling secure passwords via Deep Learning: Towards a new generation of attacks and defenses.
PhD thesis, 2021

Reducing Bias in Modeling Real-world Password Strength via Deep Learning and Dynamic Dictionaries.
Proceedings of the 30th USENIX Security Symposium, 2021

Unleashing the Tiger: Inference Attacks on Split Learning.
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

2020
BootCMatchG: An adaptive Algebraic MultiGrid linear solver for GPUs.
Softw. Impacts, 2020

AMG based on compatible weighted matching for GPUs.
Parallel Comput., 2020

Interpretable Probabilistic Password Strength Meters via Deep Learning.
Proceedings of the Computer Security - ESORICS 2020, 2020

2019
Improving Password Guessing via Representation Learning.
IACR Cryptol. ePrint Arch., 2019

Out-domain examples for generative models.
CoRR, 2019

Adversarial Out-domain Examples for Generative Models.
Proceedings of the 2019 IEEE European Symposium on Security and Privacy Workshops, 2019


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