Antonio Emanuele Cinà

Orcid: 0000-0003-3807-6417

Affiliations:
  • University of Genoa, Italy


According to our database1, Antonio Emanuele Cinà authored at least 34 papers between 2021 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Harnessing Hyperbolic Geometry for Harmful Prompt Detection and Sanitization.
CoRR, April, 2026

Evaluating the robustness of explainable AI in medical image recognition under natural and adversarial data corruption.
Mach. Learn., January, 2026

On the robustness of adversarial training against uncertainty attacks.
Pattern Recognit., 2026

Poison once, fool many: Practical poisoning attacks against text-to-image retrieval systems.
Knowl. Based Syst., 2026

HORNET: Fast and minimal adversarial perturbations.
Inf. Sci., 2026

Sonic: Fast and transferable data poisoning on clustering algorithms.
Inf. Sci., 2026

2025
Backdoor learning curves: explaining backdoor poisoning beyond influence functions.
Int. J. Mach. Learn. Cybern., March, 2025

Rethinking Robustness in Machine Learning: A Posterior Agreement Approach.
Trans. Mach. Learn. Res., 2025

Robust image classification with multi-modal large language models.
Pattern Recognit. Lett., 2025

Energy-latency attacks via sponge poisoning.
Inf. Sci., 2025

Pirates of Charity: Exploring Donation-based Abuses in Social Media Platforms.
Proceedings of the ACM on Web Conference 2025, 2025

TransferBench: Benchmarking Ensemble-based Black-box Transfer Attacks.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Evaluating the evaluators: trust in adversarial robustness tests.
Proceedings of the Joint Proceedings of the Thematic Workshops at Ital-IA 2025 colocated with the 5th National Conference on Artificial Intelligence, 2025

Code Generation of Smart Contracts with LLMs: A Case Study on Hyperledger Fabric.
Proceedings of the 36th IEEE International Symposium on Software Reliability Engineering, 2025

σ-zero: Gradient-based Optimization of ℓ0-norm Adversarial Examples.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Vulnerability Assessment of LLM-Generated Smart Contracts in Ethereum.
Proceedings of the Generative Code Intelligence Workshop (GeCoIn 2025) co-located with 28th European Conference on Artificial Intelligence (ECAI 2025), 2025

Exploring the Potential of LLMs for Code Deobfuscation.
Proceedings of the Detection of Intrusions and Malware, and Vulnerability Assessment, 2025

AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024
Machine Learning Security Against Data Poisoning: Are We There Yet?
Computer, March, 2024

Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis.
CoRR, 2024

σ-zero: Gradient-based Optimization of 𝓁<sub>0</sub>-norm Adversarial Examples.
CoRR, 2024

The Imitation Game: Exploring Brand Impersonation Attacks on Social Media Platforms.
Proceedings of the 33rd USENIX Security Symposium, 2024

Conning the Crypto Conman: End-to-End Analysis of Cryptocurrency-based Technical Support Scams.
Proceedings of the IEEE Symposium on Security and Privacy, 2024

Toward Measuring and Understanding the Overvalidation Phenomena.
Proceedings of the International Conference on Machine Learning and Applications, 2024

Understanding XAI Through the Philosopher's Lens: A Historical Perspective.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

Computing the Capacity of Discrete Channels Using Vector Flows.
Proceedings of the Dynamics of Information Systems - 7th International Conference, 2024

2023
Hardening RGB-D object recognition systems against adversarial patch attacks.
Inf. Sci., December, 2023

Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning.
ACM Comput. Surv., 2023

Vector Flows and the Capacity of a Discrete Memoryless Channel.
CoRR, 2023

Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training.
Proceedings of the Image Analysis and Processing - ICIAP 2023, 2023

On the Limitations of Model Stealing with Uncertainty Quantification Models.
Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

2022
Security of Machine Learning (Dagstuhl Seminar 22281).
Dagstuhl Reports, July, 2022

A black-box adversarial attack for poisoning clustering.
Pattern Recognit., 2022

2021
The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers?
Proceedings of the International Joint Conference on Neural Networks, 2021


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