2 papers
cs.CR2026
Defense Against Prompt Inversion Attacks: An Information-Theoretic Approach for LLM Collaborative Inference
Sayedeh Leila Noorbakhsh, Hossein Khalili, Nader Sehatbakhsh
Collaborative edge-cloud inference enables resource-constrained devices to leverage large language models (LLMs) by offloading partial computation to cloud servers. However, transm…
cs.LG2024
Learning Robust and Privacy-Preserving Representations via Information Theory
Binghui Zhang, Sayedeh Leila Noorbakhsh, Yun Dong +2
Machine learning models are vulnerable to both security attacks (e.g., adversarial examples) and privacy attacks (e.g., private attribute inference). We take the first step to miti…