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cs.CR2026

Sound Debloating of Redundant Checks in Zero-Knowledge Machine-Learning Circuits

Zhantong Xue, Pingchuan Ma, Zhaoyu Wang +3

Zero-knowledge (ZK) proof systems for neural-network inference compile the model into a system of arithmetic constraints. Many of these constraints are redundant checks: range proo…

cs.CR2026

From Shield to Target: Denial-of-Service Attacks on LLM-Based Agent Guardrails

Yuguang Zhou, Xunguang Wang, Pingchuan Ma +3

LLM-based guardrails have emerged as a highly effective defense against prompt injection and jailbreak attacks in autonomous agents. However, we reveal that the very reasoning and…

cs.CR2026

ZK-Value: A Practical Zero-Knowledge System for Verifiable Data Valuation

Zhaoyu Wang, Pingchuan Ma, Zhantong Xue +4

Data valuation is a foundational task in data marketplaces, where a Shapley-value attribution determines how a buyer's payment is distributed among data providers. Typically, the m…

cs.CR2025

RepoMark: A Data-Usage Auditing Framework for Code Large Language Models

Wenjie Qu, Yuguang Zhou, Bo Wang +4

The rapid development of Large Language Models (LLMs) for code generation has transformed software development by automating coding tasks with unprecedented efficiency. However, th…

cs.CR2025

Prompt Inversion Attack against Collaborative Inference of Large Language Models

Wenjie Qu, Yuguang Zhou, Yongji Wu +4

Large language models (LLMs) have been widely applied for their remarkable capability of content generation. However, the practical use of open-source LLMs is hindered by high reso…