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LymphNode: A Plug-and-Play Access Control Method for Deep Neural Networks

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arXiv:2605. 16227v1 Announce Type: new Abstract: Deep Neural Networks (DNNs) are high-value intellectual property (IP), yet deploying them to edge environments exposes them to \textbf{unrestricted oracle access}, rendering them vulnerable to model extraction and inversion attacks.

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Authors: Hanyu Pei, Shang Liu, Zeyan Liu
Released: 2026-05-18 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because LymphNode: A Plug-and-Play Access Control Method for Deep Neural Networks overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: text, extraction, control, model. Source: arxiv cs.CR (Cryptography and Security).
arXiv: 2605.16227

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