28 citations · 28 across the 10 of their papers we have counts for
5 papers · 1 filter
ContractLens: Latent Security Knowledge for Malicious Smart Contract Detection
Shuyi Miao, Xinyi Huang, Wangjie Qiu +4
Detecting malicious smart contracts is essential to safeguarding the Web3.0 ecosystem. However, existing auditing methods based on large language models (LLMs) largely rely on prom…
E-MIA: Exam-Style Black-Box Membership Inference Attacks against RAG Systems
Zelin Guan, Shengda Zhuo, Zeyan Li +4
Retrieval-Augmented Generation (RAG) equips large language models (LLMs) with external evidence by retrieving documents at inference time, but it also turns the retrieval corpusint…
UniDetect: LLM-Driven Universal Fraud Detection across Heterogeneous Blockchains
Shuyi Miao, Wangjie Qiu, Shengda Zhuo +5
As cross-chain interoperability advances, decentralized finance (DeFi) protocols enable illicit funds to be reorganized into uniform liquid assets that flow throughout the cryptocu…
Mask-Free Privacy Extraction and Rewriting: A Domain-Aware Approach via Prototype Learning
Xiaodong Li, Yuhua Wang, Qingchen Yu +5
Client-side privacy rewriting is crucial for deploying LLMs in privacy-sensitive domains. However, existing approaches struggle to balance privacy and utility. Full-text methods of…
Safely Learning with Private Data: A Federated Learning Framework for Large Language Model
JiaYing Zheng, HaiNan Zhang, LingXiang Wang +3
Private data, being larger and quality-higher than public data, can greatly improve large language models (LLM). However, due to privacy concerns, this data is often dispersed in m…