3 papers
cs.CR2026
Towards Privacy-Preserving Federated Learning using Hybrid Homomorphic Encryption
Ivan Costa, Pedro Correia, Ivone Amorim +2
Federated Learning (FL) enables collaborative training while keeping sensitive data on clients' devices, but local model updates can still leak private information. Hybrid Homomorp…
cs.CR2026
A Systematic Literature Review on LLM Defenses Against Prompt Injection and Jailbreaking: Expanding NIST Taxonomy
Pedro H. Barcha Correia, Ryan W. Achjian, Diego E. G. Caetano de Oliveira +5
The rapid advancement and widespread adoption of generative artificial intelligence (GenAI) and large language models (LLMs) has been accompanied by the emergence of new security v…
cs.CR2025
Federated Learning: An approach with Hybrid Homomorphic Encryption
Pedro Correia, Ivan Silva, Ivone Amorim +2
Federated Learning (FL) is a distributed machine learning approach that promises privacy by keeping the data on the device. However, gradient reconstruction and membership-inferenc…