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F. Almeida

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#federated learning Open access Oct 2026

Overcoming Memory Bottlenecks in Homomorphic Federated Learning: A Chunk-Based Serverless MapReduce Approach

Federated Learning (FL) enables collaborative model training across decentralized organizations without direct data sharing, yet communicating raw gradient updates remains susceptible to reconstruction and membership inference attacks. Fully Homomorphic Encryption (FHE) provides cryptographic privacy during aggregation...

Afonso Cruz, Carlos Marques, Vasco Carvalho et al. · 0 citations
Review Open access Aug 2026

An Integrated Honeypot and LLM-Based Framework for near Real-Time Detection and Behavioral Analysis of Malicious Activities

Integration of deterministic preprocessing with LLM-based reasoning enables the transformation of raw honeypot logs into structured and actionable cybersecurity intelligence, reducing analyst workload while improving the explainability and reliability of intrusion analysis in near-real-time environments.

Rúben Oliveira, Tiago Gomes, D. Pinho et al. · 0 citations

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