4 papers
A Novel Semantic Manifold Alignment Attack against Embedding-to-Embedding Obfuscation in Privacy-Preserving LLMs
Sicong Li, Lingfeng Yao, Xingke Yang +7
With the widespread applications of large language models (LLMs), privacy-preserving inference has become increasingly essential for sensitive queries. To balance privacy and utili…
WebWeaver: Breaking Topology Confidentiality in LLM Multi-Agent Systems with Stealthy Context-Based Inference
Zixun Xiong, Gaoyi Wu, Lingfeng Yao +3
Communication topology is a critical factor in the utility and safety of LLM-based multi-agent systems (LLM-MAS), making it a high-value intellectual property (IP) whose confidenti…
pFedNavi: Structure-Aware Personalized Federated Vision-Language Navigation for Embodied AI
Qingqian Yang, Hao Wang, Sai Qian Zhang +6
Vision-Language Navigation VLN requires large-scale trajectory instruction data from private indoor environments, raising significant privacy concerns. Federated Learning FL mitiga…
iSeal: Encrypted Fingerprinting for Reliable LLM Ownership Verification
Zixun Xiong, Gaoyi Wu, Qingyang Yu +5
Given the high cost of large language model (LLM) training from scratch, safeguarding LLM intellectual property (IP) has become increasingly crucial. As the standard paradigm for I…