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cs.CR2026
TIGER: Inverting Transformer Gradients via Embedding-Subspace Distance Optimization
William Kalikman, Ivo Petrov, Dimitar I. Dimitrov +1
Federated learning allows multiple clients to jointly train a shared model by sending gradient updates to a central server while keeping raw inputs local. However, prior gradient i…
cs.CR2026
Honeyval: A Comprehensive Evaluation Framework for LLM-powered HTTP Honeypots
Mark Vero, Fabian Kaczmarczyck, Ivan Petrov +6
Honeypots are decoy systems mimicking real system components designed to defend against cyber attacks. Recently, LLMs increasingly serve as simulation backbones for honeypots. They…